Beyond ventricular fibrillation analysis: Comprehensive waveform analysis for all cardiac rhythms occurring during resuscitation

被引:13
作者
Alonso, Erik [1 ,2 ]
Eftestol, Trygve [1 ]
Aramendi, Elisabete [2 ]
Kramer-Johansen, Jo [3 ,4 ]
Skogvoll, Eirik [5 ,6 ]
Nordseth, Trond [5 ,6 ]
机构
[1] Univ Stavanger, Dept Elect Engn & Comp Sci, N-4036 Stavanger, Norway
[2] Univ Basque Country UPV EHU, Dept Commun Engn, Bilbao 48013, Spain
[3] Oslo Univ Hosp, Norwegian Natl Advisory Unit Prehosp Emergency Me, N-0424 Oslo, Norway
[4] Univ Oslo, N-0424 Oslo, Norway
[5] Norwegian Univ Sci & Technol NTNU, Inst Circulat & Med Imaging, N-7491 Trondheim, Norway
[6] St Olavs Univ Hosp, Dept Anesthesia & Intens Care Med, N-7014 Trondheim, Norway
关键词
Cardiac arrest; Electrocardiogram (ECG); ECG waveform analysis; Rhythm transition classifier; AUTOMATED EXTERNAL DEFIBRILLATION; BASIC LIFE-SUPPORT; CARDIOPULMONARY-RESUSCITATION; COUNTERSHOCK SUCCESS; STATE TRANSITIONS; EXECUTIVE-COMMITTEE; GUIDELINES; 2000; OXYGEN UPTAKE; WORKING GROUP; PREDICTION;
D O I
10.1016/j.resuscitation.2014.08.022
中图分类号
R4 [临床医学];
学科分类号
1002 ; 100602 ;
摘要
Aim: To propose a method which analyses the electrocardiogram (ECG) waveform of any cardiac rhythm occurring during resuscitation and computes the probability of that rhythm converting into another with better prognosis (Pdes). Methods: Rhythm transitions occurring spontaneously or due to defibrillation were analyzed. For each possible rhythm, ventricular fibrillation/ventricular tachycardia (VF/VT), pulseless electrical activity (PEA), pulse-generating rhythm (PR) and asystole (AS), the desired and undesired transitions were defined. ECG segments corresponding to the last 3s of rhythms prior to transition were used to extract waveform features. For each rhythm type, waveform features were combined into a logistic regression model to develop a rhythm specific classifier of desired transitions. This model was the monitoring function for the _Pdes. The capacity of each rhythm specific classifier to discriminate between desired and undesired transitions was evaluated in terms of area under the curve (AUC). _Pdes was integrated into a state sequence representation, which structures the information of cardiac arrest episodes, to analyze the effect of therapy on patient. As a case study, the effect of optimal/suboptimal cardiopulmonary resuscitation (CPR) on Ades was analyzed. The mean Ades was computed for the pre- and post-CPR intervals which presented the same underlying rhythm. The relationship between the optimal/suboptimal CPR and increase/decrease of Ades was analyzed. Results: The AUC was 0.80, 0.79, 0.73 and 0.61 for VF/VT, PEA, PR and AS respectively. The Ades quantified the probability of every rhythm of the episode developing to a better state, and the evolution of Pdes was coherent with the provided therapy. The case study indicated, for most rhythms, that positive trends in the dynamic behaviour could be associated with optimal CPR, whereas the opposite seemed true for negative trends. Conclusion: A method for continuous ECG waveform analysis covering all cardiac rhythms during resuscitation has been proposed. This methodology can be further developed to be used in retrospective studies of CPR techniques, and, in the future, for potentially monitoring in real time the probability of survival of patients being resuscitated. (C) 2014 Elsevier Ireland Ltd. All rights reserved.
引用
收藏
页码:1541 / 1548
页数:8
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