title: [Analysis of ventricular fibrillation signals for the evaluation of defibrillation success in the treatment of ventricular fibrillation].
abstract: OBJECTIVE
  Precise detection of ventricular fibrillation (VF), reliable prediction of defibrillation success and adjustment of the discharge waveform to the patient's transthoracic impedance may contribute to a reduction of electricity-associated myocardial injury caused by unnecessary counter shocks. Specifically, asystole thresholds distinguish between VF and asystole, and thus prevent unnecessary defibrillation attempts. We reviewed various studies and manufacturer characteristics regarding the parameters and algorithms for analyzing arrhythmia ECG signals.
  
  
  METHODS
  Asystole threshold values of several defibrillator manufacturers were collected and a literature review was performed including the following parameters: amplitude, frequency, bispectral analysis, amplitude spectrum area, wavelets, nonlinear dynamics, N(alpha)histograms, and combinations of various parameters.
  
  
  RESULTS
  The manufacturer dependent asystole thresholds vary substantially. We show ways to optimize an ECG-based analysis for the next technological generation of defibrillators. During advanced cardiac life support (ACLS) the probability of defibrillation success should be estimated. Optimal defibrillation waveform, depending on transthoracic resistance, should be individually determined. In case of prolonged VF with a low ECG amplitude defibrillation should not be attempted unless coronary perfusion has been improved by further measures of ACLS. The combined evaluation of VF amplitude and frequency is effective in predicting defibrillation success. Estimation of further parameters is potentially useful for guiding optimal timing of defibrillation. At present, the implementation of most parameters in out-of-hospital cardiopulmonary resuscitation (CPR) is limited by the lack of technical feasibility of online computing.
  
  
  CONCLUSIONS
  Analysis of VF ECG signals should allow adequate VF detection as well as prediction of defibrillation success. Suitable asystole thresholds for analysis of ECG signals have to be determined, and the adverse effects of CPR associated artefacts on data analysis have to be reduced. Analysis of VF ECG signals is a precondition of individually optimized defibrillation and may contribute substantially to an increased quality of CPR.
authors.affiliation: Universitätsklinik für Anästhesie und Allgemeine Intensivmedizin, Leopold-Franzens Universität Innsbruck, Innsbruck, Austria.
authors.forename: W
authors.initials: W
authors.lastname: Lederer
authors.forename: K
authors.initials: K
authors.lastname: Rheinberger
authors.forename: V
authors.initials: V
authors.lastname: Lischke
authors.forename: A
authors.initials: A
authors.lastname: Amann
mesh_terms: D000465:Algorithms; D002307:Cardiography, Impedance; D016887:Cardiopulmonary Resuscitation; D004554:Electric Countershock / Q000295:instrumentation*; D004562:Electrocardiography; D004569:Electroencephalography / Q000187:drug effects; D006323:Heart Arrest; D006801:Humans; D016896:Treatment Outcome; D014693:Ventricular Fibrillation / Q000175:diagnosis* / Q000628:therapy*