Background-Defibrillator shocks often fail to terminate ventricular fibrillation (VF) in out-of-hospital cardiac arrest (OOHCA), and repeated failed shocks can worsen the subsequent response to therapy. Because the VF waveform changes with increasing duration of VF, it is possible that ECG analyses could estimate the preshock likelihood of defibrillation success. This study examined whether an amplitude-independent measure of preshock VF waveform morphology predicts outcome after defibrillation. Methods and Results-Clinical data and ECG recordings from an automated external defibrillator were obtained for 75 subjects with OOHCA in a suburban community with police first responders and a paramedic-based emergency medical system. An estimate of the fractal self-similarity dimension, the scaling exponent, was calculated off-line for the VF waveform preceding shocks. Success of the first shock was determined from the recordings. Return of pulses and survival were determined by chart review. The first shock resulted in an organized rhythm in 43% of cases, and 17% of cases survived to hospital discharge. A lower mean value of the scaling exponent was observed for cases in which the first defibrillation resulted in an organized rhythm (Pϭ0.004), for cases with return of pulses (Pϭ0.049), and for cases surviving to hospital discharge (PϽ0.001). Receiver operator curves revealed the utility of the scaling exponent for predicting the probability of restoring an organized rhythm (area under the curveϭ0.70) and of survival (area under the curveϭ0.84). Conclusions-The VF waveform in OOHCA can be quantified with the scaling exponent, which predicts the probability of first-shock defibrillation and survival to hospital discharge.

Background— The scaling exponent (ScE) of the ventricular fibrillation (VF) waveform correlates with duration of VF and predicts defibrillation outcome. We compared 4 therapeutic approaches to the treatment of VF of various durations. Methods and Results— Seventy-two swine (19.5 to 25.7 kg) were randomly assigned to 1 of 9 groups (n=8 each). VF was induced and left untreated until the ScE reached 1.10, 1.20, 1.30, or 1.40. Animals were treated with either immediate countershock (IC); 3 minutes of CPR before the first countershock (CPR); CPR for 2 minutes, then drugs given with 3 more minutes of CPR before the first shock (CPR-D); or drugs given at the start of CPR with 3 minutes of CPR before the first shock (Drugs+CPR). Return of spontaneous circulation (ROSC) and 1-hour survival were analyzed with χ 2 and Kaplan-Meier survival curves. IC was effective when the ScE was low but had decreasing success as the ScE increased. No animals in the 1.30 or 1.40 groups had ROSC from IC (0 of 16). CPR did not improve first shock outcome in the 1.20 CPR group (3 of 8 ROSC). Kaplan-Meier survival analyses indicated that IC significantly delayed time to ROSC in both the 1.3 ( P =0.0006) and the 1.4 ( P =0.005) groups. Conclusions— VF of brief to moderate duration is effectively treated by IC. When VF is prolonged, as indicated by an ScE of 1.3 or greater, IC was not effective and delayed time to ROSC. The ScE can help in choosing the first intervention in the treatment of VF.

Background: Quantitative measures of the ventricular fibrillation (VF) electrocardiogram (ECG) waveform can assess myocardial physiology and predict cardiac arrest outcomes, making these measures a candidate to help guide resuscitation. Chest compressions are typically paused for waveform measure calculation, as compressions cause ECG artifact. However, such pauses contradict resuscitation guideline recommendations to minimize CPR interruptions. We evaluated a comprehensive group of VF measures with and without ongoing compressions to determine their performance under both conditions for predicting functionally-intact survival, the study’s primary outcome. Methods: Five-second VF ECG segments were collected with and without chest compressions prior to 2755 defibrillation shocks from 1151 out-of-hospital cardiac arrest patients. Twenty-four individual measures and three combination measures were implemented. Measures were optimized to predict functionally-intact survival (Cerebral Performance Category score ≤ 2) using 460 training cases, and their performance evaluated using 691 independent test cases. Results: Measures predicted functionally-intact survival on test data with an area under the receiver operating characteristic curve (AUC) ranging from 0.56-0.75 (median=0.73) without chest compressions and from 0.53-0.75 (median=0.69) with compressions (p<0.001 for difference). Of all measures evaluated, the support vector machine model ranked highest both without chest compressions (AUC=0.75, 95% CI 0.73-0.78) and with compressions (AUC=0.75, 95% CI 0.72-0.78) (p=0.75 for difference). Conclusions: VF waveform measures predict functionally-intact survival when calculated during chest compressions, but prognostic performance is generally reduced compared to compression-free analysis. However, support vector machine models exhibited similar performance with and without compressions while also achieving the highest AUC. Such machine learning models may therefore offer means to guide resuscitation during uninterrupted CPR.

Ventricular fibrillation (VF) is the most common arrhythmia causing sudden cardiac death. However, the likelihood of successful defibrillation declines with increasing duration of VF. Because the morphology of the electrocardiogram (ECG) waveform during VF also changes with time, this study examined a new measure that describes the VF waveform and distinguishes between early and late VF. Surface ECG recordings were digitized at 200 samples/s from nine swine with induced VF. A new measure called the scaling exponent was calculated by examining the power-law relationship between the summation of amplitudes of a 1,024-point (5.12 second) waveform segment and the time scale of measurement. The scaling exponent is a local estimate of the fractal dimension of the ECG waveform. A consistent power-law relationship was observed for measurement time scales of 0.005-0.040 seconds. Calculation of the scaling exponent produced similar results between subjects, and distinguished early VF (< 4-minute duration) from late VF (> or = 4-minute duration). The scaling exponent was dependent on the order of the data, supporting the hypothesis that the surface ECG during VF is a deterministic rather than a random signal. The waveform of VF results from the interaction of multiple fronts of depolarization within the heart, and may be described using the tools of nonlinear dynamics. As a quantitative descriptor of waveform structure, the scaling exponent characterizes the time dependent organization of VF.