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Free keywords:
Ventricular fibrillation; Electrocardiography; Algorithm; Fast Fourier transformation; Shock; Return of spontaneous circulation
Abstract:
Background: Noninvasive prediction of defibrillation success after cardiac arrest and cardiopulmonary resuscitation (CPR) may help in determining the optimal time for a countershock, and thus increase the chance for survival. Methods: In a porcine model (n=25) of prolonged cardiac arrest, advanced cardiac life support was provided by administration of two or three doses of either vasopressin or epinephrine after 3 or 8 min of basic life support. After 4 min of ventricular fibrillation and 18 min of life support, defibrillation was attempted. The denoised power spectral density of 10 s intervals of the ventricular fibrillation electrocardiogram (ECG) was estimated from averaged and smoothed Fourier transforms. We have eliminated the spectral contribution of artifacts from manual chest compressions and provide a definition for the contribution of ventricular fibrillation to the power spectral density. This contribution is quantified and termed “fibrillation power”. Results: We tested fibrillation power and two established methods in their discrimination of survivors (n=16) vs. non-survivors (n=9) in the last minute before the countershock. A fibrillation power ⩾79 dB predicted successful defibrillation with sensitivity, specificity, positive predictive value and negative predictive value of 98%, 98%, 99% and 97% while a mean fibrillation frequency ⩾7.7 Hz was predictive with 85%, 83%, 90% and 77% and a mean amplitude ⩾0.49 mV was predictive with 95%, 90%, 94% and 91%. Conclusions: We suggest that fibrillation power is an alternative source of information on the status of a fibrillating heart and that it may match the established mean frequency and amplitude analysis of ECG in predicting successful countershock during CPR.
