Analyse von Flimmersignalen zur Abschätzung der Defibrillierbarkeit beim Kammerflimmern

Zusammenfassung

Ziel der Studie: Die präzise Erkennung von Kammerflimmern (KF), die richtige Einschätzung der Defibrillierbarkeit und die Anpassung des Defibrillationspulses an den transthorakalen Widerstand können Strom-assoziierte Myokardschäden von unnötigen Defibrillationen vermeiden. Die herstellerspezifischen EKG-Amplitudenschwellwerte zur Abgrenzung von Asystolie und Ergebnisse verschiedener Studien über die Verwendbarkeit von passenden Parametern und Algorithmen zur Analyse von EKG Signalen beim KF wurden evaluiert. Methodik: Eine Hersteller- und Literaturüberblicksarbeit mit folgenden Parametern wurde durchgeführt: Amplitude, Frequenz, Bispektralanalyse, Fläche des Amplitudenspektrums, nicht-lineare Dynamik, N(α)-Histogramme, sowie eine Kombination von mehreren Parametern. Ergebnisse: Die EKG-Amplitudenschwellwerte zur Abgrenzung der Asystolie von KF sind bei den handelsüblichen Defibrillatoren unterschiedlich festgelegt. Wir stellen Möglichkeiten vor, wie die EKG-Analyse der nächste Defibrillatorgeneration optimiert werden könnte. Im Rahmen der erweiterten Wiederbelebungsmaßnahmen sollte die Wahrscheinlichkeit für einen Defibrillationserfolg abgeschätzt werden können. Die optimale Form des Defibrillationspulses sollte mittels des transthorakalen Widerstandes individuell bestimmbar sein. Beim prolongierten KF mit niedriger Amplitude sollte die Defibrillation erst versucht werden, nachdem die Koronararterienperfusion durch erweiterte Maßnahmen der Reanimation verbessert wurde und die charakteristischen Parameter des Flimmersignals zugenommen haben. Die kombinierte Auswertung von Flimmeramplitude und Flimmerfrequenz kann den Defibrillationserfolg genauer vorhersagen. Unter Einbindung weiterer Parameter könnte die Bestimmung des optimalen Defibrillationszeitpunktes optimiert werden. Die Anwendbarkeit der meisten Parameter unter Prähospitalbedingungen der kardiopulmonalen Wiederbelebung (CPR) wird derzeit durch die fehlende technische Machbarkeit einer online-Auswertung begrenzt. Schlussfolgerung: Die Flimmersignalanalyse sollte sowohl eine adäquate Flimmererkennung als auch eine verlässliche Vorhersage des Defibrillationserfolges ermöglichen. Passende Schwellwerte müssen festgelegt und Störeinflüsse von Reanimationsmaßnahmen auf die Datenanalyse vermindert werden. Die Flimmersignalanalyse ist eine Voraussetzung für eine individuell optimale Effektivität der Defibrillation und kann wesentlich zur Qualitätssteigerung der CPR beitragen.

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(α)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. Conclusion: 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.

Schlüsselwörter

CPR - Defibrillation - EKG - Myokardschädigung - Kammerflimmern

Key words

CPR - defibrillation - ECG - myocardial injury - ventricular fibrillation

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