Dynamics and state transitions during resuscitation in out-of-hospital cardiac arrest

被引:44
|
作者
Skogvoll, Eirik [1 ,2 ]
Eftestol, Trygve [3 ]
Gundersen, Kenneth [3 ]
Kvaloy, Jan Terje [4 ]
Kramer-Johansen, Jo [5 ,6 ]
Olasveengen, Theresa Mariero [5 ,6 ]
Steen, Petter Andreas [5 ,6 ]
机构
[1] St Olavs Univ Hosp, Dept Anesthesiol & Emergency Med, N-7006 Trondheim, Norway
[2] Norwegian Univ Sci & Technol NTNU, Fac Med, Unit Appl Clin Res, Trondheim, Norway
[3] Univ Stavanger, Fac Sci & Technol, Dept Elect & Comp Engn, Stavanger, Norway
[4] Univ Stavanger, Fac Sci & Technol, Dept Math & Nat Sci, Stavanger, Norway
[5] Ullevaal Univ Hosp, Expt Med Res Inst, Oslo, Norway
[6] Ullevaal Univ Hosp, Dept Anesthesiol, Oslo, Norway
关键词
cardiopulmonary resuscitation; cardiac arrest; Markov model;
D O I
10.1016/j.resuscitation.2008.02.015
中图分类号
R4 [临床医学];
学科分类号
1002 ; 100602 ;
摘要
Background: The state or rhythm during resuscitation, i.e. ventricular fibrillation/tachycardia (VF/VT), asystole (ASY), pulseless electrical. activity (PEA), or return of spontaneous circulation (ROSC) determines management. The state is unstable and will. change either spontaneously (e.g. PEA -> ASY) or by intervention (e.g. VF -> ASY after DC shock); temporary ROSC may also occur. To gain insight into the dynamics of this process, we analyzed the state transitions over time using real-life data. Methods: Detailed recordings from 304 episodes of attempted resuscitation from out-of-hospital cardiac arrests of presumed cardiac etiology were obtained from modified Heartstart (R) 4000 defibrillators. State transitions were visualized and described, and analyzed in terms of a Markov probability model. Results: The median number of state transitions was 5 (range 1-39), and more transitions were observed with VF than PEA or asystole as the initial rhythm. Of 105 patients (35%) who regained ROSC at some point during CPR, only 65 (21 %) achieved sustained ROSC; suggesting an unrealized survival potential. A 3-min transition probability matrix was estimated: for example, a patient early in VF has a probability of 31% to be in ASY, 32% of still being in VF, 5% to have temporary ROSC, and 2% to have sustained ROSC after 3 min. Conclusion: The dynamics of resuscitation can be described in terms of state transitions and a Markov probability model. This framework enables prediction of short-term clinical development, supports informed decisions during CPR, and suggests a novel area for research. (c) 2008 Elsevier Ireland Ltd. All rights reserved.
引用
收藏
页码:30 / 37
页数:8
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