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

Resuscitation. 2008 Jul;78(1):30-7. doi: 10.1016/j.resuscitation.2008.02.015. Epub 2008 Apr 10.

Abstract

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 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.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Cardiopulmonary Resuscitation / methods*
  • Electrocardiography
  • Heart Arrest / physiopathology
  • Heart Arrest / therapy*
  • Humans
  • Markov Chains
  • Prospective Studies
  • Survival Rate