• Anton Amann, Klaus Rheinberger, Ulrich Achleitner, Anette C Krismer, Werner Lingnau, Karl H Lindner, and Volker Wenzel.
• Department of Anesthesiology and Critical Care Medicine, Leopold-Franzens-University Innsbruck, Anichstrasse 35, 6020 Innsbruck, Austria. anton.amann@uibk.ac.at
• Anesth. Analg. 2002 Sep 1;95(3):716-22, table of contents.

UnlabelledWe estimated the predictive power with respect to defibrillation outcome of ventricular fibrillation (VF) mean frequency (FREQ), mean peak-to-trough amplitude (AMPL), and their combination. We examined VF electrocardiogram signals of 64 pigs from 4 different cardiac arrest models with different durations of untreated VF, different durations of cardiopulmonary resuscitation, and use of different drugs (epinephrine, vasopressin, N-nitro-L-arginine methyl ester, or saline placebo). The frequency domain was restricted to the range from 4.33 to 30 Hz. In the 10-s epoch between 20 and 10 s before the first defibrillation shock, FREQ and AMPL were estimated. We introduced the survival index (SI; 0.68 Hz(-1). FREQ + 12.69 mV(-1). AMPL) by use of multiple logistic regression. Kruskal-Wallis nonparametric one-way analysis was used to analyze the different porcine models for significant difference. The variables FREQ, AMPL, and SI were compared with defibrillation outcome by means of univariate logistic regression and receiver operating characteristic curves. SI increased predictive power compared with AMPL or FREQ alone, resulting in 89% sensitivity and 86% specificity. The probabilities of predicting defibrillation outcome for FREQ, AMPL, and SI were 0.85, 0.89 and 0.90, respectively. FREQ, AMPL, and SI values were not sensitive in regard to the four different cardiac arrest models but were significantly different for vasopressin and epinephrine animals.ImplicationsWe present a retrospective data analysis to evaluate the predictive power of different ventricular fibrillation electrocardiogram variables in pigs with respect to defibrillation outcome. We showed that our combination of variables leads to an improved forecast, which may help to reduce harmful unsuccessful defibrillation attempts.

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