Literature DB >> 23603153

Clinical state transitions during advanced life support (ALS) in in-hospital cardiac arrest.

Trond Nordseth1, Daniel Bergum, Dana P Edelson, Theresa M Olasveengen, Trygve Eftestøl, Rune Wiseth, Benjamin S Abella, Eirik Skogvoll.   

Abstract

BACKGROUND: When providing advanced life support (ALS) in cardiac arrest, the patient may alternate between four clinical states: ventricular fibrillation/tachycardia (VF/VT), pulseless electrical activity (PEA), asystole, and return of spontaneous circulation (ROSC). At the end of the resuscitation efforts, either death has been declared or sustained ROSC has been obtained. The aim of this study was to describe and analyze the clinical state transitions during ALS among patients experiencing in-hospital cardiac arrest. METHODS AND
RESULTS: The defibrillator files from 311 in-hospital cardiac arrests at the University of Chicago Hospital (IL, USA) and St. Olav University Hospital (Trondheim, Norway) were analyzed (clinicaltrials.gov: NCT00920244). The transitions between clinical states were annotated along the time axis and visualized as plots of the state prevalence according to time. The cumulative intensity of the state transitions was estimated by the Nelson-Aalen estimator for each type of state transition, and for the intensities of overall state transitions. Between 70% and 90% of patients who eventually obtained sustained ROSC had progressed to ROSC by approximately 15-20 min of ALS, depending on the initial rhythm. Patients behaving unstably after this time period, i.e., alternating between ROSC, VF/VT and PEA, had a high risk of ultimately being declared dead.
CONCLUSIONS: We provide an overall picture of the intensities and patterns of clinical state transitions during in-hospital ALS. The majority of patients who obtained sustained ROSC obtained this state and stabilized within the first 15-20 min of ALS. Those who continued to behave unstably after this time point had a high risk of ultimately being declared dead.
Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.

Entities:  

Keywords:  Cardiac arrest; Cardiopulmonary resuscitation; Dynamics; Statistics

Mesh:

Year:  2013        PMID: 23603153     DOI: 10.1016/j.resuscitation.2013.04.010

Source DB:  PubMed          Journal:  Resuscitation        ISSN: 0300-9572            Impact factor:   5.262


  4 in total

1.  Impact of 'synchronous' and 'asynchronous' CPR modality on quality bundles and outcome in out-of-hospital cardiac arrest patients.

Authors:  Gianfranco Sanson; Giuseppe Ristagno; Giuseppe Davide Caggegi; Athina Patsoura; Veronica Xu; Marco Zambon; Domenico Montalbano; Sreten Vukanovic; Vittorio Antonaglia
Journal:  Intern Emerg Med       Date:  2019-07-04       Impact factor: 3.397

2.  State transition modeling of complex monitored health data.

Authors:  Jörn Schulz; Jan Terje Kvaløy; Kjersti Engan; Trygve Eftestøl; Samwel Jatosh; Hussein Kidanto; Hege Ersdal
Journal:  J Appl Stat       Date:  2019-12-04       Impact factor: 1.416

3.  Mixed convolutional and long short-term memory network for the detection of lethal ventricular arrhythmia.

Authors:  Artzai Picon; Unai Irusta; Aitor Álvarez-Gila; Elisabete Aramendi; Felipe Alonso-Atienza; Carlos Figuera; Unai Ayala; Estibaliz Garrote; Lars Wik; Jo Kramer-Johansen; Trygve Eftestøl
Journal:  PLoS One       Date:  2019-05-20       Impact factor: 3.240

4.  Towards the Prediction of Rearrest during Out-of-Hospital Cardiac Arrest.

Authors:  Andoni Elola; Elisabete Aramendi; Enrique Rueda; Unai Irusta; Henry Wang; Ahamed Idris
Journal:  Entropy (Basel)       Date:  2020-07-09       Impact factor: 2.524

  4 in total

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