The median frequency of the ECG during ventricular fibrillation: its use in an algorithm for estimating the duration of cardiac arrest.

Abstract

Recent studies have suggested that the initial therapeutic intervention for ventricular fibrillation (VF) may depend on downtime (DT), i.e., the time duration of VF. We characterized the dynamics of the frequency distribution in the power spectrum of the ECG recorded from eleven swine during VF to determine if enough information existed in this domain to estimate DT. We used the median frequency (FM) of the power spectrum to track the frequency distribution. The FM followed a dynamic repeatable course during the first 10 min of VF. Intersubject variability was small. We modeled the FM data of the eleven subjects with a set of first-order polynomial equations and tested the algorithm with data from an additional ten subjects. The algorithm predicted VF duration with an average error of -0.86 min; 71.5% of the predictions fell within the 95% confidence limits of the model. This paper has identified a signal processing tool which may be useful in the prehospital treatment of VF.