Predicting the success of defibrillation by electrocardiographic analysis

Artificial intelligence for predicting shockable rhythm during cardiopulmonary resuscitation: In-hospital setting

AIM OF THE STUDY

This study aimed to develop an artificial intelligence (AI) model capable of predicting shockable rhythms from electrocardiograms (ECGs) with compression artifacts using real-world data from emergency department (ED) settings. Additionally, we aimed to explore the black box nature of AI models, providing explainability.

METHODS

This study is retrospective, observational study using a prospectively collected database. Adult patients who presented to the ED with cardiac arrest or experienced cardiac arrest in the ED between September 2021 and February 2024 were included. ECGs with a compression artifact of 5 s before every rhythm check were used for analysis. The AI model was designed based on convolutional neural networks. The ECG data were assigned into training, validation, and testing sets on a per-patient basis to ensure that ECGs from the same patient did not appear in multiple sets. Gradient-weighted class activation mapping was employed to demonstrate AI explainability.

RESULTS

A total of 1,889 ECGs with compression artifacts from 172 patients were used. The area under the receiver operating characteristic curve (AUROC) for shockable rhythm prediction was 0.8672 (95% confidence interval [CI]: 0.8161-0.9122). The AUROCs for manual and mechanical compression were 0.8771 (95% CI: 0.8054-0.9408) and 0.8466 (95% CI: 0.7630-0.9138), respectively.

CONCLUSION

This study was the first to accurately predict shockable rhythms during compression using an AI model trained with actual patient ECGs recorded during resuscitation. Furthermore, we demonstrated the explainability of the AI. This model can minimize interruption of cardiopulmonary resuscitation and potentially lead to improved outcomes.

Estimation of invasive coronary perfusion pressure using electrocardiogram and Photoplethysmography in a porcine model of cardiac arrest

BACKGROUND

Coronary perfusion pressure (CPP) indicates spontaneous return of circulation and is recommended for high-quality cardiopulmonary resuscitation (CPR). This study aimed to investigate a method for non-invasive estimation of CPP using electrocardiography (ECG) and photoplethysmography (PPG) during CPR.

METHODS

Nine pigs were used in this study. ECG, PPG, invasive arterial blood pressure (ABP), and right atrial pressure (RAP) signals were simultaneously recorded. The CPPs were estimated using three datasets: (a) ECG, (b) PPG, and (c) ECG and PPG, and were compared with invasively measured CPPs. Four machine-learning algorithms, namely support vector regression, random forest (RF), K-nearest neighbor, and gradient-boosted regression tree, were used for estimation of CPP.

RESULTS

The RF model with a combined ECG and PPG dataset achieved better estimation of CPP than the other algorithms. Specifically, the mean absolute error was 4.49 mmHg, the root mean square error was 6.15 mm Hg, and the adjusted R2 was 0.75. A strong correlation was found between the non-invasive estimation and invasive measurement of CPP (r = 0.88), which supported our hypothesis that machine-learning-based analysis of ECG and PPG parameters can provide a non-invasive estimation of CPP for CPR.

CONCLUSIONS

This study proposes a novel estimation of CPP using ECG and PPG with machine-learning-based algorithms. Non-invasively estimated CPP showed a high correlation with invasively measured CPP and may serve as an easy-to-use physiological indicator for high-quality CPR treatment.

Ventricular fibrillation waveform properties influenced by thoracic impedance guided chest compressions in a porcine model

BACKGROUND AND OBJECTIVE

Quantitative measures extracted from ventricular fibrillation (VF) waveform reflect the metabolic state of the myocardium and are associated with survival outcome. The quality of delivered chest compressions during cardiopulmonary resuscitation are also linked with survival. The aim of this research is to explore the viability and effectiveness of a thoracic impedance (TI) based chest compression (CC) guidance system to control CC depth within individual subjects and influence VF waveform properties.

METHODS

This porcine investigation includes an analysis of two protocols. CC were delivered in 2 min episodes at a constant rate of 110 CC min-1. Subject-specific CC depth was controlled using a TI-thresholding system where CC were performed according to the amplitude (ZRMS, 0.125 to 1.250 Ω) of a band-passed TI signal (ZCC). Protocol A was a retrospective analysis of a 12-porcine study to characterise the response of two VF waveform metrics: amplitude spectrum area (AMSA) and mean slope (MS), to varying CC quality. Protocol B was a prospective 12-porcine study to determine if changes in VF waveform metrics, due to CC quality, were associated with defibrillation outcome.

RESULTS

Protocol A: A directly proportional relationship was observed between ZRMS and CC depth applied within each subject (r = 0.90; p <0.001). A positive relationship was observed between ZRMS and both AMSA (p <0.001) and MS (p <0.001), where greater TI thresholds were associated with greater waveform metrics.

PROTOCOL B

MS was associated with return of circulation following defibrillation (odds ratio = 2.657; p = 0.043).

CONCLUSION

TI-thresholding was an effective way to control CC depth within-subjects. Compressions applied according to higher TI thresholds evoked an increase in AMSA and MS. The response in MS due to deeper CC resulted in a greater incidence of ROSC compared to shallow chest compressions.

Instantaneous amplitude: Association of ventricular fibrillation waveform measures at time of shock with outcome in out-of-hospital cardiac arrest

BACKGROUND

Prompt defibrillation is key to successful resuscitation from ventricular fibrillation out-of-hospital cardiac arrest (VF-OHCA). Preliminary evidence suggests that the timing of shock relative to the amplitude of the VF ECG waveform may affect the likelihood of resuscitation. We investigated whether the VF waveform amplitude at the time of shock (instantaneous amplitude) predicts outcome independent of other validated waveform measures.

METHODS

We conducted a retrospective study of VF-OHCA patients ≥18 old. We evaluated three VF waveform measures for each shock: instantaneous amplitude at the time of shock, and maximum amplitude and amplitude spectrum area (AMSA) over a 3-s window preceding the shock. Linear mixed-effects modeling was used to determine whether instantaneous amplitude was associated with shock-specific return of organized rhythm (ROR) or return of spontaneous circulation (ROSC) independent of maximum amplitude or AMSA.

RESULTS

The 566 eligible patients received 1513 shocks, resulting in ROR of 62.0% (938/1513) and ROSC of 22.3% (337/1513). In unadjusted regression, an interquartile increase in instantaneous amplitude was associated with ROR (Odds ratio [OR] [95% confidence interval] = 1.27 [1.11-1.45]) and ROSC (OR = 1.27 [1.14-1.42]). However, instantaneous amplitude was not associated with ROR (OR = 1.13 [0.97-1.30]) after accounting for maximum amplitude, nor with ROR (OR = 1.00 [0.87-1.15]) or ROSC (OR = 1.05 [0.93-1.18]) after accounting for AMSA. By contrast, AMSA and maximum amplitude remained independently associated with ROR and ROSC.

CONCLUSIONS

We did not observe an independent association between instantaneous amplitude and shock-specific outcomes. Efforts to time shock to the maximal amplitude of the VF waveform are unlikely to affect resuscitation outcome.

Patterned Illumination Techniques in Optogenetics: An Insight Into Decelerating Murine Hearts

Much has been reported about optogenetic based cardiac arrhythmia treatment and the corresponding characterization of photostimulation parameters, but still, our capacity to interact with the underlying spatiotemporal excitation patterns relies mainly on electrical and/or pharmacological approaches. However, these well-established treatments have always been an object of somehow heated discussions. Though being acutely life-saving, they often come with potential side-effects leading to a decreased functionality of the complex cardiac system. Recent optogenetic studies showed the feasibility of the usage of photostimulation as a defibrillation method with comparatively high success rates. Although, these studies mainly concentrated on the description as well as on the comparison of single photodefibrillation approaches, such as locally focused light application and global illumination, less effort was spent on the description of excitation patterns during actual photostimulation. In this study, the authors implemented a multi-site photodefibrillation technique in combination with Multi-Lead electrocardiograms (ECGs). The technical connection of real-time heart rhythm measurements and the arrhythmia counteracting light control provides a further step toward automated arrhythmia classification, which can lead to adaptive photodefibrillation methods. In order to show the power effectiveness of the new approach, transgenic murine hearts expressing channelrhodopsin-2 ex vivo were investigated using circumferential micro-LED and ECG arrays. Thus, combining the best of two methods by giving the possibility to illuminate either locally or globally with differing pulse parameters. The optical technique presented here addresses a number of challenges of technical cardiac optogenetics and is discussed in the context of arrhythmic development during photostimulation.

Targeted Delivery of Electrical Shocks and Epinephrine, Guided by Ventricular Fibrillation Amplitude Spectral Area, Reduces Electrical and Adrenergic Myocardial Burden, Improving Survival in Swine

Background

We previously reported that resuscitation delivering electrical shocks guided by real‐time ventricular fibrillation amplitude spectral area (AMSA) enabled return of spontaneous circulation (ROSC) with fewer shocks, resulting in less myocardial dysfunction. We now hypothesized that AMSA could also guide delivery of epinephrine, expecting further outcome improvement consequent to less electrical and adrenergic burdens.

Methods and Results

A swine model of ventricular fibrillation was used to compare after 10 minutes of untreated ventricular fibrillation a guidelines‐driven (n=8) resuscitation protocol, delivering shocks every 2 minutes and epinephrine every 4 minutes, with an AMSA‐driven shocks (n=8) protocol, delivering epinephrine every 4 minutes, and with an AMSA‐driven shocks and epinephrine (ADSE; n=8) protocol. For guidelines‐driven, AMSA‐driven shocks, and ADSE protocols, the time to ROSC (mean±SD) was 569±164, 410±111, and 400±80 seconds (P=0.045); the number of shocks (mean±SD) was 5±2, 3±1, and 3±2 (P=0.024) with ADSE fewer than guidelines‐driven (P=0.03); and the doses of epinephrine (median [interquartile range]) were 2.0 (1.3–3.0), 1.0 (1.0–2.8), and 1.0 (0.3–3.0) (P=0.419). The ROSC rate was similar, yet survival after ROSC favored AMSA‐driven protocols (guidelines‐driven, 3/6; AMSA‐driven shocks, 6/6; and ADSE, 7/7; P=0.019 by log‐rank test). Left ventricular function and survival after ROSC correlated inversely with electrical burden (ie, cumulative unsuccessful shocks, J/kg; P=0.020 and P=0.046) and adrenergic burden (ie, total epinephrine doses, mg/kg; P=0.042 and P=0.002).

Conclusions

Despite similar ROSC rates achieved with all 3 protocols, AMSA‐driven shocks and ADSE resulted in less postresuscitation myocardial dysfunction and better survival, attributed to attaining ROSC with less electrical and adrenergic myocardial burdens.

[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.

Effect of Amplitude Spectral Area on Termination of Fibrillation and Outcomes in Pediatric Cardiac Arrest

Background

Amplitude spectral area (AMSA) predicts termination of fibrillation (TOF) with return of spontaneous circulation (ROSC) and survival in adults but has not been studied in pediatric cardiac arrest. We characterized AMSA during pediatric cardiac arrest from a Pediatric Resuscitation Quality Collaborative and hypothesized that AMSA would be associated with TOF and ROSC.

Methods and Results

Children aged <18 years with cardiac arrest and ventricular fibrillation were studied. AMSA was calculated for 2 seconds before shock and averaged for each subject (AMSA‐avg). TOF was defined as termination of ventricular fibrillation 10 seconds after defibrillation to any non‐ventricular fibrillation rhythm. ROSC was defined as >20 minutes without chest compressions. Univariate and multivariable logistic regression analyses controlling for weight, current, and illness category were performed. Primary end points were TOF and ROSC. Secondary end points were 24‐hour survival and survival to discharge. Between 2015 and 2019, 50 children from 14 hospitals with 111 shocks were identified. In univariate analyses AMSA was not associated with TOF and AMS‐Aavg was not associated with ROSC. Multivariable logistic regression showed no association between AMSA and TOF but controlling for defibrillation average current and illness category, there was a trend to significant association between AMSA‐avg and ROSC (odds ratio, 1.10 [1.00‒1.22] P=0.058). There was no significant association between AMSA‐avg and 24‐hour survival or survival to hospital discharge.

Conclusions

In pediatric patients, AMSA was not associated with TOF, whereas AMSA‐avg had a trend to significance for association in ROSC, but not 24‐hour survival or survival to hospital discharge.

Registration

URL: https://www.clinicaltrials.gov; Unique identifier: NCT02708134.

Estimating the amplitude spectrum area of ventricular fibrillation during cardiopulmonary resuscitation using only ECG waveform

Background

Amplitude spectrum area (AMSA) calculated from ventricular fibrillation (VF) can be used to monitor the effectiveness of chest compression (CC) and optimize the timing of defibrillation. However, reliable AMSA can only be obtained during CC pause because of artifacts. In this study, we sought to develop a method for estimating AMSA during cardiopulmonary resuscitation (CPR) using only the electrocardiogram (ECG) waveform.

Methods

Intervals of 8 seconds ECG and CC-related references, including 4 seconds during CC and an adjacent 4 seconds without CC, were collected before 1,008 defibrillation shocks from 512 out-of-hospital cardiac arrest patients. Signal quality was analyzed based on the irregularity of autocorrelation of VF. If signal quality index (SQI) was high, AMSA would be calculated from the original signal. Otherwise, CC-related artifacts would be constructed and suppressed using the least mean square filter from VF before calculation of AMSA. The algorithm was optimized using 480 training shocks and evaluated using 528 independent testing shocks.

Results

Overall, CC resulted in lower SQI [0.15 (0.04-0.61) with CC vs. 0.75 (0.61-0.83) without CC, P<0.01] and higher AMSA [11.2 (7.7-16.2) with CC vs. 7.2 (4.9-10.6) mVHz without CC, P<0.01] values. The predictive accuracy (49.2% vs. 66.5%, P<0.01) and area under the receiver operating characteristic curve (AUC) (0.647 vs. 0.734, P<0.01) were significantly decreased during CC. Using the proposed method, the estimated AMSA was 7.1 (5.0-15.2) mVHz, the predictive accuracy was 67.0% and the AUC was 0.713, which were all comparable with those calculated without CC.

Conclusions

Using the signal quality-based artifact suppression method, AMSA can be reliably estimated and continuously monitored during CPR.

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.

Cardioplegia defibrillation of circulatory and metabolic phase ventricular fibrillation in a swine model

INTRODUCTION

We previously found potassium cardioplegia followed by rapid calcium reversal (Kplegia) can achieve defibrillation in a swine model of electrical phase of ventricular fibrillation (VF) comparable to standard care.

HYPOTHESIS

Exploring 3 possible potassium dose and timing protocols, we hypothesize Kplegia may benefit resuscitation of longer duration untreated VF.

METHODS

Three separate blinded randomized placebo-controlled trials were performed with electrically-induced VF untreated for durations of 6, 9, and 12min in a swine model. Experimental groups received infusion of 1 or 2 boluses of intravenous (IV) potassium followed by a single calcium reversal bolus. Potassium was replaced by saline in the control groups. Outcomes included: amplitude spectrum area (AMSA) during VF, resulting rhythms, number of defibrillations, return of spontaneous circulation (ROSC), and hemodynamics for 1h post ROSC. Binomial and interval data outcomes were compared with exact statistics. Serial interval data were assessed with mixed regression models.

RESULTS

Twelve, 12, and 8 animals were included at 6, 9, and 12min VF durations for a total of 32. ROSC was achieved in: 4/6 Kplegia and 3/6 control animals in the 6min protocol, (p=1.00), 4/6 Kplegia and 2/6 control animals in the 9min protocol,(p=0.57), and 0/5 Kplegia and 1/3 control animals in the 12min protocol,(p=0.38). Two of 8 Kplegia animals achieved ROSC with chemical defibrillation alone.

CONCLUSIONS

The majority of animals achieved ROSC after up to 9min of untreated VF arrest using K plegia protocols. K plegia requires further optimization for both peripheral IV and intraosseous infusion, and to assess for superiority over standard care. Institutional Animal Care and Use Committee protocol #15127224.

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

BACKGROUND AND AIM

Unsuccessful defibrillation shocks adversely affect survival from out-of-hospital cardiac arrest (OHCA). Ventricular fibrillation (VF) waveform analysis is the tool-of-choice for the non-invasive prediction of shock success, but surrogate markers of perfusion like end-tidal CO2 (EtCO2) could improve the prediction. The aim of this study was to evaluate EtCO2 as predictor of shock success, both individually and in combination with VF-waveform analysis.

MATERIALS AND METHODS

In total 514 shocks from 214 OHCA patients (75 first shocks) were analysed. For each shock three predictors of defibrillation success were automatically calculated from the device files: two VF-waveform features, amplitude spectrum area (AMSA) and fuzzy entropy (FuzzyEn), and the median EtCO2 (MEtCO2) in the minute before the shock. Sensitivity, specificity, receiver operating characteristic (ROC) curves and area under the curve (AUC) were calculated, for each predictor individually and for the combination of MEtCO2 and VF-waveform predictors. Separate analyses were done for first shocks and all shocks.

RESULTS

MEtCO2 in first shocks was significantly higher for successful than for unsuccessful shocks (31mmHg/25mmHg, p<0.05), but differences were not significant for all shocks (32mmHg/29mmHg, p>0.05). MEtCO2 predicted shock success with an AUC of 0.66 for first shocks, but was not a predictor for all shocks (AUC 0.54). AMSA and FuzzyEn presented AUCs of 0.76 and 0.77 for first shocks, and 0.75 and 0.75 for all shocks. For first shocks, adding MEtCO2 improved the AUC of AMSA and FuzzyEn to 0.79 and 0.83, respectively.

CONCLUSIONS

MEtCO2 predicted defibrillation success only for first shocks. Adding MEtCO2 to VF-waveform analysis in first shocks improved prediction of shock success. VF-waveform features and MEtCO2 were automatically calculated from the device files, so these methods could be introduced in current defibrillators adding only new software.

Amplitude screening improves performance of AMSA method for predicting success of defibrillation in swine model

PURPOSE

A novel amplitude screening method, termed Optimal Amplitude Spectrum Area (Opt-AMSA) with the aim of improving the performance of the Amplitude Spectrum Area (AMSA) method, was proposed to optimize the timing of defibrillation. We investigated the effects of the Opt-AMSA method on the prediction of successful defibrillation when compared with AMSA in a porcine model of ventricular fibrillation (VF).

METHOD

60 male domestic pigs were untreated in the first 10 min of VF, then received cardiopulmonary resuscitation (CPR) for 6 min. Values of Opt-AMSA and AMSA were calculated every minute before defibrillation. Linear regression was used to evaluate the correlation between Opt-AMSA and AMSA. Receiver Operating Characteristic (ROC) analysis was conducted for the two methods and to compare their predictive values.

RESULTS

The values of both AMSA and Opt-AMSA gradually decreased over time during untreated VF in all animals. The values of both methods of defibrillation were slightly increased after the implementation of CPR in animals that were successfully resuscitated, while there were no significant changes in either method in those who ultimately failed to resuscitate. The significant positive correlation between Opt-AMSA and AMSA was shown by Pearson correlation analysis. ROC analysis showed that Opt-AMSA (AUC = 0.87) significantly improved the performance of AMSA (AUC = 0.77) to predict successful defibrillation (Z = 2.27, P < 0.05).

CONCLUSION

Both the Opt-AMSA and AMSA methods showed high potential to predict the success of defibrillation. Moreover, the Opt-AMSA method improved the performance of the AMSA method, and may be a promising tool to optimize the timing of defibrillation.

Correlation of end tidal carbon dioxide, amplitude spectrum area, and coronary perfusion pressure in a porcine model of cardiac arrest

Amplitude Spectrum Area (AMSA) values during ventricular fibrillation (VF) correlate with myocardial energy stores and predict defibrillation success. By contrast, end tidal CO₂ (ETCO2) values provide a noninvasive assessment of coronary perfusion pressure and myocardial perfusion during cardiopulmonary resuscitation (CPR). Given the importance of the timing of defibrillation shock delivery on clinical outcome, we tested the hypothesis that AMSA and ETCO2 correlate with each other and can be used interchangably to correlate with myocardial perfusion in an animal laboratory preclinical, randomized, prospective investigation. After 6 min of untreated VF, 12 female pigs (32 ± 1 Kg), isoflurane anesthetized pigs received sequentially 3 min periods of standard (S) CPR, S‐CPR+ an impedance threshold device (ITD), and then active compression decompression (ACD) + ITD CPR. Hemodynamic, AMSA, and ETCO2 measurements were made with each method of CPR. The Spearman correlation and Friedman tests were used to compare hemodynamic parameters. ETCO2, AMSA, coronary perfusion pressure, cerebral perfusion pressure were lowest with STD CPR, increased with STD CPR + ITD and highest with ACD CPR + ITD. Further analysis demonstrated a positive correlation between AMSA and ETCO2 (r = 0.37, P = 0.025) and between AMSA and key hemodynamic parameters (P < 0.05). This study established a moderate positive correlation between ETCO2 and AMSA. These findings provide the physiological basis for developing and testing a novel noninvasive method that utilizes either ETCO2 alone or the combination of ETCO2 and AMSA to predict when defibrillation might be successful.

Real-Time Ventricular Fibrillation Amplitude-Spectral Area Analysis to Guide Timing of Shock Delivery Improves Defibrillation Efficacy During Cardiopulmonary Resuscitation in Swine

Background

The ventricular fibrillation amplitude spectral area (AMSA) predicts whether an electrical shock could terminate ventricular fibrillation and prompt return of spontaneous circulation. We hypothesized that AMSA can guide more precise timing for effective shock delivery during cardiopulmonary resuscitation.

Methods and Results

Three shock delivery protocols were compared in 12 pigs each after electrically induced ventricular fibrillation, with the duration of untreated ventricular fibrillation evenly stratified into 6, 9, and 12 minutes: AMSA‐Driven (AD), guided by an AMSA algorithm; Guidelines‐Driven (GD), according to cardiopulmonary resuscitation guidelines; and Guidelines‐Driven/AMSA‐Enabled (GDAE), as per GD but allowing earlier shocks upon exceeding an AMSA threshold. Shocks delivered using the AD, GD, and GDAE protocols were 21, 40, and 62, with GDAE delivering only 2 AMSA‐enabled shocks. The corresponding 240‐minute survival was 8/12, 6/12, and 2/12 (log‐rank test, P=0.035) with AD exceeding GDAE (P=0.026). The time to first shock (seconds) was (median [Q1–Q3]) 272 (161–356), 124 (124–125), and 125 (124–125) (P<0.001) with AD exceeding GD and GDAE (P<0.05); the average coronary perfusion pressure before first shock (mm Hg) was 16 (9–30), 10 (6–12), and 3 (−1 to 9) (P=0.002) with AD exceeding GDAE (P<0.05); and AMSA preceding the first shock (mV·Hz, mean±SD) was 13.3±2.2, 9.0±1.6, and 8.6±2.0 (P<0.001) with AD exceeding GD and GDAE (P<0.001). The AD protocol delivered fewer unsuccessful shocks (ie, less shock burden) yielding less postresuscitation myocardial dysfunction and higher 240‐minute survival.

Conclusions

The AD protocol improved the time precision for shock delivery, resulting in less shock burden and less postresuscitation myocardial dysfunction, potentially improving survival compared with time‐fixed, guidelines‐driven, shock delivery protocols.

A method to differentiate between ventricular fibrillation and asystole during chest compressions using artifact-corrupted ECG alone

In recent years, numerous adaptive filtering techniques have been developed to suppress the chest compression (CC) artifact for reliable analysis of the electrocardiogram (ECG) rhythm without CC interruption. Unfortunately, the result of rhythm diagnosis during CCs is still unsatisfactory in many studies. The misclassification between corrupted asystole (ASY) and corrupted ventricular fibrillation (VF) is generally regarded as one of the major reasons for the poor performance of reported methods. In order to improve the diagnosis of VF/ASY corrupted by CCs, a novel method combining a least mean-square (LMS) filter and an amplitude spectrum area (AMSA) analysis was developed based only on the analysis of the surface of the corrupted ECG episode. This method was tested on 253 VF and 160 ASY ECG samples from subjects who experienced cardiac arrest using a porcine model and was compared with six other algorithms. The validation results indicated that this method, which yielded a satisfactory result with a sensitivity of 93.3%, a specificity of 96.3% and an accuracy of 94.8%, is superior to the other reported techniques. After improvement using the human ECG records in real cardiopulmonary resuscitation (CPR) scenarios, the algorithm is promising for corrupted VF/ASY detection with no hardware alterations in clinical practice.

Energy conserving chemical defibrillation of ventricular fibrillation: A randomized two phase controlled blinded trial

OBJECTIVES

Potassium cardioplegia-induced transient asystole may conserve myocardial energy, foster chemical defribrillation, and improve VF arrest outcome. A trial of potassium infusion with or without calcium reversal was conducted to test for improvement in intra-arrest VF waveform and post-ROSC hemodynamics.

METHODS

Eighteen swine were randomized to three treatment arms in two phases. VF was electrically induced and untreated for 4min. The animals then received 6min of mechanical CPR. Blinded investigators infused two study medicines peripherally during this interval. One group received 1.5mEq/kg KCl with CPR initiation followed 3min later by CaCl 10% infusion 0.12cm(3)/kg, the second group received 1.5mEq/kg KCl without CaCl, and the third group received placebo infusions. Ten minutes post VF initiation, defibrillation was performed, as appropriate, followed by ACLS for continued arrest or observation for 30min if ROSC. AMSA change from before to 5min post study drug infusion was compared with nonparametric statistics. MAP post ROSC was compared using mixed linear regression analysis.

RESULTS

Average normalized AMSA change was -0.15, -0.63, and +0.27 in the KCl, KCl+CaCl, and placebo groups, respectively (p=0.01). Three KCl+CaCl animals developed on organized rhythm chemically without electrical defibrillation. One, 3, and 4 animals in the KCl, KCl+CaCl, and placebo groups, respectively, survived post ROSC. Post ROSC, MAP decreased 1.8mmHg (95% CI -1.4 to 5.1) min(-1) less in the KCl+CaCl group compared to placebo.

CONCLUSIONS

Chemical defibrillation and ROSC are possible post potassium-induced asystole. Potassium followed by calcium reversal, but not potassium alone, led to ROSC and post-ROSC hemodynamics comparable to recommended therapy.

Integration of Attributes from Non-Linear Characterization of Cardiovascular Time-Series for Prediction of Defibrillation Outcomes

Objective

The timing of defibrillation is mostly at arbitrary intervals during cardio-pulmonary resuscitation (CPR), rather than during intervals when the out-of-hospital cardiac arrest (OOH-CA) patient is physiologically primed for successful countershock. Interruptions to CPR may negatively impact defibrillation success. Multiple defibrillations can be associated with decreased post-resuscitation myocardial function. We hypothesize that a more complete picture of the cardiovascular system can be gained through non-linear dynamics and integration of multiple physiologic measures from biomedical signals.

Materials and Methods

Retrospective analysis of 153 anonymized OOH-CA patients who received at least one defibrillation for ventricular fibrillation (VF) was undertaken. A machine learning model, termed Multiple Domain Integrative (MDI) model, was developed to predict defibrillation success. We explore the rationale for non-linear dynamics and statistically validate heuristics involved in feature extraction for model development. Performance of MDI is then compared to the amplitude spectrum area (AMSA) technique.

Results

358 defibrillations were evaluated (218 unsuccessful and 140 successful). Non-linear properties (Lyapunov exponent > 0) of the ECG signals indicate a chaotic nature and validate the use of novel non-linear dynamic methods for feature extraction. Classification using MDI yielded ROC-AUC of 83.2% and accuracy of 78.8%, for the model built with ECG data only. Utilizing 10-fold cross-validation, at 80% specificity level, MDI (74% sensitivity) outperformed AMSA (53.6% sensitivity). At 90% specificity level, MDI had 68.4% sensitivity while AMSA had 43.3% sensitivity. Integrating available end-tidal carbon dioxide features into MDI, for the available 48 defibrillations, boosted ROC-AUC to 93.8% and accuracy to 83.3% at 80% sensitivity.

Conclusion

At clinically relevant sensitivity thresholds, the MDI provides improved performance as compared to AMSA, yielding fewer unsuccessful defibrillations. Addition of partial end-tidal carbon dioxide (PetCO₂) signal improves accuracy and sensitivity of the MDI prediction model.

The ventricular fibrillation waveform approach to direct postshock chest compressions in a swine model of VF arrest

BACKGROUND

In retrospective swine and human investigations of ventricular fibrillation (VF) cardiac arrest, the amplitude-spectral area (AMSA), determined from the VF waveform, can predict defibrillation and a return of spontaneous circulation (ROSC).

OBJECTIVES

We hypothesized that an algorithm using AMSA in real time to direct postshock chest compression (CC) duration would shorten the time to ROSC and improve neurological outcome in a swine model of VF cardiac arrest with acute myocardial infarction (AMI) or nonischemic myocardium.

METHODS

AMI was induced by occlusion of the left anterior descending artery. VF was untreated for 10 min. Animals were randomized to either traditional resuscitation with 2 min of CC after each shock or to an AMSA-guided algorithm where postshock CCs were shortened to 1 min if the preshock AMSA exceeded 20 mV-Hz.

RESULTS

A total of 48 animals were studied, 12 in each group (AMI vs. normal, and traditional vs. AMSA-guided). There was a nonsignificant shorter time to ROSC with an AMSA-guided approach in AMI swine (17.2 ± 3.4 vs. 18.5 ± 4.7 min, p = NS), and in normal swine (13.5 ± 1.1 vs. 14.4 ± 1.2, p = NS). Neurological outcome was similar between traditional and AMSA-guided animals. AMSA predicted ROSC (p < 0.001), and a threshold of 20 mV-Hz gave a sensitivity of 89%, with specificity of 29%.

CONCLUSION

Although AMSA predicts ROSC in a swine model of VF arrest in both AMI and normal swine, a waveform-guided approach that uses AMSA to direct postshock CC duration does not significantly shorten the time to ROSC or alter neurological outcome.

Association of amplitude spectral area of the ventricular fibrillation waveform with survival of out-of-hospital ventricular fibrillation cardiac arrest

BACKGROUND

Previous investigations of out-of-hospital cardiac arrest (OHCA) have shown that the waveform characteristic amplitude spectral area (AMSA) can predict successful defibrillation and return of spontaneous circulation (ROSC) but has not been studied previously for survival.

OBJECTIVES

To determine whether AMSA computed from the ventricular fibrillation (VF) waveform is associated with pre-hospital ROSC, hospital admission, and hospital discharge.

METHODS

Adults with witnessed OHCA and an initial rhythm of VF from an Utstein style database were studied. AMSA was measured prior to each shock and averaged for each subject (AMSA-avg). Factors such as age, sex, number of shocks, time from dispatch to monitor/defibrillator application, first shock AMSA, and AMSA-avg that could predict pre-hospital ROSC, hospital admission, and hospital discharge were analyzed by logistic regression.

RESULTS

Eighty-nine subjects (mean age 62 ± 15 years) with a total of 286 shocks were analyzed. AMSA-avg was associated with pre-hospital ROSC (p = 0.003); a threshold of 20.9 mV-Hz had a 95% sensitivity and a 43.4% specificity. Additionally, AMSA-avg was associated with hospital admission (p < 0.001); a threshold of 21 mV-Hz had a 95% sensitivity and a 54% specificity and with hospital discharge (p < 0.001); a threshold of 25.6 mV-Hz had a 95% sensitivity and a 53% specificity. First-shock AMSA was also predictive of pre-hospital ROSC, hospital admission, and discharge. Time from dispatch to monitor/defibrillator application was associated with hospital admission (p = 0.034) but not pre-hospital ROSC or hospital discharge.

CONCLUSIONS

AMSA is highly associated with pre-hospital ROSC, survival to hospital admission, and hospital discharge in witnessed VF OHCA. Future studies are needed to determine whether AMSA computed during resuscitation can identify patients for whom continuing current resuscitation efforts would likely be futile.

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.

Median frequencies of prolonged ventricular fibrillation treated by V-A ECMO correspond to a return of spontaneous circulation rate

BACKGROUND

The aim of our study was to analyze, in a pig model of prolonged ventricular fibrillation (VF) treated by veno-arterial extracorporeal membrane oxygenation (ECMO), the time dependent changes of VF wavelet frequency obtained from intracardial signals and its relations to return of spontaneous circulation (ROSC).

METHODS

11 female pigs (50.3 ± 3.4 kg) under general anesthesia had undergone 15 min of VF with ECMO flow of 5 to 10 ml/kg per min simulating "untreated" VF followed by continued VF with full ECMO flow of 100 ml/kg per min. The median frequency (MF) of VF from right ventricular apex, coronary perfusion pressure, myocardial oxygen metabolism and resuscitability were determined.

RESULTS

Median (interquartile range) of MF of fibrillatory wavelets in minute 15 of low ECMO flow [9.7 Hz (8.3; 10.1)] was not significantly changed in comparison to minute 1 [10.5 Hz (9.8; 12.4)], p = 0.12. Five minutes after full ECMO initiation MF increased [11.6 Hz (10.6; 13.5)], p = 0.04 (compared to minute 15 of VF) and did not deteriorate during the rest of ECMO treatment. Out of all subjects, three animals did not reach ROSC. Those subjects demonstrated deeper decrease of MF at the VF minute 15 as compared to others [-2.4 Hz (-2.5; -2.3) vs. -0.6 Hz (-1.6; -0.1)] and continuously significantly higher increase in MF on full ECMO support [4.3 Hz (2.9; 5.6) vs. 1.1 Hz (0.6; 1.6)] with p = 0.05 for both observations, respectively.

CONCLUSIONS

The veno-arterial ECMO reperfusion influences MF of VF wavelet obtained from right ventricular apex. The course of changes in wavelet frequency corresponds to a presence of later ROSC.

Advanced life support therapy on out-of-hospital cardiac arrest patients: an engineering perspective

In the USA alone, several hundred thousand people die of sudden cardiac arrests each year. Basic life support, defined as chest compressions and ventilations, and early defibrillation are the only factors proven to increase the survival of patients with out-of-hospital cardiac arrest and are key elements in the chain of survival defined by the American Heart Association. The current cardiopulmonary resuscitation guidelines treat all patients the same but studies show a need for more individualization of treatment. This review focusses on ideas on how to strengthen the weak parts of the chain of survival including the ability to measure the effects of therapy, improve time efficiency and optimize the sequence and quality of the various components of cardiopulmonary resuscitation.

Rhythm analysis during cardiopulmonary resuscitation: past, present, and future

Survival from out-of-hospital cardiac arrest depends largely on two factors: early cardiopulmonary resuscitation (CPR) and early defibrillation. CPR must be interrupted for a reliable automated rhythm analysis because chest compressions induce artifacts in the ECG. Unfortunately, interrupting CPR adversely affects survival. In the last twenty years, research has been focused on designing methods for analysis of ECG during chest compressions. Most approaches are based either on adaptive filters to remove the CPR artifact or on robust algorithms which directly diagnose the corrupted ECG. In general, all the methods report low specificity values when tested on short ECG segments, but how to evaluate the real impact on CPR delivery of continuous rhythm analysis during CPR is still unknown. Recently, researchers have proposed a new methodology to measure this impact. Moreover, new strategies for fast rhythm analysis during ventilation pauses or high-specificity algorithms have been reported. Our objective is to present a thorough review of the field as the starting point for these late developments and to underline the open questions and future lines of research to be explored in the following years.

A support vector machine for predicting defibrillation outcomes from waveform metrics

BACKGROUND

Algorithms to predict shock success based on VF waveform metrics could significantly enhance resuscitation by optimising the timing of defibrillation.

OBJECTIVE

To investigate robust methods of predicting defibrillation success in VF cardiac arrest patients, by using a support vector machine (SVM) optimisation approach.

METHODS

Frequency-domain (AMSA, dominant frequency and median frequency) and time-domain (slope and RMS amplitude) VF waveform metrics were calculated in a 4.1Y window prior to defibrillation. Conventional prediction test validity of each waveform parameter was conducted and used AUC>0.6 as the criterion for inclusion as a corroborative attribute processed by the SVM classification model. The latter used a Gaussian radial-basis-function (RBF) kernel and the error penalty factor C was fixed to 1. A two-fold cross-validation resampling technique was employed.

RESULTS

A total of 41 patients had 115 defibrillation instances. AMSA, slope and RMS waveform metrics performed test validation with AUC>0.6 for predicting termination of VF and return-to-organised rhythm. Predictive accuracy of the optimised SVM design for termination of VF was 81.9% (± 1.24 SD); positive and negative predictivity were respectively 84.3% (± 1.98 SD) and 77.4% (± 1.24 SD); sensitivity and specificity were 87.6% (± 2.69 SD) and 71.6% (± 9.38 SD) respectively.

CONCLUSIONS

AMSA, slope and RMS were the best VF waveform frequency-time parameters predictors of termination of VF according to test validity assessment. This a priori can be used for a simplified SVM optimised design that combines the predictive attributes of these VF waveform metrics for improved prediction accuracy and generalisation performance without requiring the definition of any threshold value on waveform metrics.

Electrocardiogram frequency change by extracorporeal blood perfusion in a swine ventricular fibrillation model

Background

Extracorporeal cardiopulmonary resuscitation (ECPR) refers to the application of extracorporeal blood circulation with oxygenation as a resuscitation tool. The objective of this study is to observe the frequency component changes in the electrocardiogram (ECG) by ECPR during prolonged ventricular fibrillation (VF).

Methods

Six swine were prepared as a VF model. Extracorporeal blood circulation with a pulsatile blood pump and oxygenator was set up for the model. ECG signals were measured for 13 min during VF and analyzed using frequency analysis methods. The median frequency (MF), dominant frequency (DF), and amplitude spectrum area (AMSA) were calculated from a spectrogram obtained using short-time Fourier transform (STFT).

Results

MF decreased from 11 Hz at the start to 9 Hz at 2 min after VF and then increased to 11 Hz at 4.5 min after VF. DF started at 7 Hz and increased to 11 Hz within the first min and decreased to 9 Hz at 2 min, then increased to 12 Hz at 4.5 min after VF. Both frequency components decreased gradually from 4.5 min until 10 min after VF. After the oxygenated blood perfusion was initiated, both MF and DF increased remarkably and exceeded 12 and 14 Hz, respectively. Similarly, AMSA decreased gradually for the first 10 min, but increased remarkably and varied beyond 13 mV∙Hz after the oxygenated blood supply started. Remarkable frequency increases in ECG due to the oxygenated blood perfusion during ECPR were observed in the swine VF model.

Conclusions

The ECG frequency analysis during ECPR can give the resuscitation provider important information about the cardiac perfusion status and the appropriateness of the ECPR setup as well as the prediction of defibrillation success.

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.

A new method to estimate the amplitude spectrum analysis of ventricular fibrillation during cardiopulmonary resuscitation

AIMS

Accurate ventricular fibrillation (VF) waveform analysis usually requires rescuers to discontinue cardiopulmonary resuscitation (CPR). However, prolonged "hands-off" time has a deleterious impact on the outcome. We developed a new filter technique that could clean the CPR artifacts and help preserve the shockability index of VF METHODS: We analyzed corrupted ECGs, which were constructed by randomly adding different scaled CPR artifacts to the VF waveforms. A newly developed algorithm was used to identify the CPR fluctuations. The algorithm contained two steps. First, decomposing the raw data by empirical mode decomposition (EMD) into several intrinsic mode fluctuations (IMFs) and combining the dominant IMFs to reconstruct a new signal. Second, calculating each CPR cycle frequency from the new signal and fitting the new signal to the original corrupted ECG by least square mean (LSM) method to derive the CPR artifacts. The estimated VF waveform was derived by subtraction of the CPR artifacts from the corrupted ECG. We then performed amplitude spectrum analysis (AMSA) for original VF, corrupted ECG and estimated VF.

RESULTS

A total of 150 OHCA subjects with initial VF rhythm were included for analysis. Ten CPR artifacts signals were used to construct corrupted ECG. Even though the correlations of AMSA between the corrupted ECG vs. the original VF and the estimated VF vs. the original VF are all high (all p<0.001), the values of AMSA were obviously biased in corrupted ECG with wide limits of agreement in Bland-Altman mean-difference plot. ROC analysis of the AMSA in the prediction of defibrillation success showed that the new algorithm could preserve the cut-off AMSA value for CPR artifacts with power ratio to VF from 0 to 6 dB.

CONCLUSION

The new algorithm could efficiently filter the CPR-related artifacts of the VF ECG and preserve the shockability index of the original VF waveform.

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.

Evolution of activation patterns during long-duration ventricular fibrillation in pigs

Quantitative analysis has demonstrated five temporal stages of activation during the first 10 min of ventricular fibrillation (VF) in dogs. To determine whether these stages exist in another species, we applied the same analysis to the first 10 min of VF recorded in vivo from two 504-electrode arrays, one each on left anterior and posterior ventricular epicardium in six anesthetized pigs. The following descriptors were continuously quantified: 1) number of wavefronts, 2) wavefront fractionations, 3) wavefront collisions, 4) repeatability, 5) multiplicity index, 6) wavefront conduction velocity, 7) activation rate, 8) mean area activated by the wavefronts, 9) negative peak rate of voltage change, 10) incidence of breakthrough/foci, 11) incidence of block, and 12) incidence of reentry. Cluster analysis of these descriptors divided VF into four stages (stages i-iv). The values of most descriptors increased during stage i (1-22 s after VF induction), changed quickly to values indicating greater organization during stage ii (23-39 s), decreased steadily during stage iii (40-187 s), and remained relatively unchanged during stage iv (188-600 s). The epicardium still activated during stage iv instead of becoming silent as in dogs. In conclusion, during the first 10 min, VF activation can be divided into four stages in pigs instead of five stages as in dogs. Following a 16-s period during the first minute of VF when activation became more organized, all parameters exhibited progressive decreased organization. Further studies are warranted to determine whether these changes, particularly the increased organization of stage ii, have clinical consequences, such as alteration in defibrillation efficacy.