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Electroencephalography (EEG) for neurological prognostication after cardiac arrest and targeted temperature management; rationale and study design

Westhall, Erik LU ; Rosén, Ingmar LU ; Rossetti, Andrea O.; van Rootselaar, Anne-Fleur; Kjaer, Troels Wesenberg; Horn, Janneke; Ullen, Susann; Friberg, Hans LU ; Nielsen, Niklas and Cronberg, Tobias LU (2014) In BMC Neurology 14.
Abstract
Background: Electroencephalography (EEG) is widely used to assess neurological prognosis in patients who are comatose after cardiac arrest, but its value is limited by varying definitions of pathological patterns and by inter-rater variability. The American Clinical Neurophysiology Society (ACNS) has recently proposed a standardized EEG-terminology for critical care to address these limitations. In the Target Temperature Management (TTM) trial, a large international trial on temperature management after cardiac arrest, EEG-examinations were part of the prospective study design. The main objective of this study is to evaluate EEG-data from the TTM-trial and to identify malignant EEG-patterns reliably predicting a poor neurological outcome.... (More)
Background: Electroencephalography (EEG) is widely used to assess neurological prognosis in patients who are comatose after cardiac arrest, but its value is limited by varying definitions of pathological patterns and by inter-rater variability. The American Clinical Neurophysiology Society (ACNS) has recently proposed a standardized EEG-terminology for critical care to address these limitations. In the Target Temperature Management (TTM) trial, a large international trial on temperature management after cardiac arrest, EEG-examinations were part of the prospective study design. The main objective of this study is to evaluate EEG-data from the TTM-trial and to identify malignant EEG-patterns reliably predicting a poor neurological outcome. Methods/Design: In the TTM-trial, 399 post cardiac arrest patients who remained comatose after rewarming underwent a routine EEG. The presence of clinical seizures, use of sedatives and antiepileptic drugs during the EEG-registration were prospectively documented. After the end of the trial, the EEGs were retrieved to form a central EEG-database. The EEG-data will be analysed using the ACNS EEG terminology. We designed an electronic case record form (eCRF). Four EEG-specialists from different countries, blinded to patient outcome, will independently classify the EEGs and report through the eCRF. We will describe the prognostic values of pre-specified EEG patterns to predict poor as well as good outcome. We hypothesise three patterns to always be associated with a poor outcome (suppressed background without discharges, suppressed background with continuous periodic discharges and burst-suppression). Inter- and intra-rater variability and whether sedation or level of temperature affects the prognostic values will also be analyzed. Discussion: A well-defined terminology for interpreting post cardiac arrest EEGs is critical for the use of EEG as a prognostic tool. The results of this study may help to validate the ACNS terminology for assessing post cardiac arrest EEGs and identify patterns that could reliably predict outcome. (Less)
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author
organization
publishing date
type
Contribution to journal
publication status
published
subject
keywords
EEG, Prognosis, Interrater variability, Brain injury, Out-of-hospital, cardiac arrest, Hypothermia, Resuscitation
in
BMC Neurology
volume
14
publisher
BioMed Central
external identifiers
  • wos:000340644900001
  • scopus:84906832161
ISSN
1471-2377
DOI
10.1186/s12883-014-0159-2
language
English
LU publication?
yes
id
d222d53a-81ef-41ef-813e-462928dc68d7 (old id 4656279)
date added to LUP
2014-10-01 07:25:42
date last changed
2017-02-19 03:43:10
@article{d222d53a-81ef-41ef-813e-462928dc68d7,
  abstract     = {Background: Electroencephalography (EEG) is widely used to assess neurological prognosis in patients who are comatose after cardiac arrest, but its value is limited by varying definitions of pathological patterns and by inter-rater variability. The American Clinical Neurophysiology Society (ACNS) has recently proposed a standardized EEG-terminology for critical care to address these limitations. In the Target Temperature Management (TTM) trial, a large international trial on temperature management after cardiac arrest, EEG-examinations were part of the prospective study design. The main objective of this study is to evaluate EEG-data from the TTM-trial and to identify malignant EEG-patterns reliably predicting a poor neurological outcome. Methods/Design: In the TTM-trial, 399 post cardiac arrest patients who remained comatose after rewarming underwent a routine EEG. The presence of clinical seizures, use of sedatives and antiepileptic drugs during the EEG-registration were prospectively documented. After the end of the trial, the EEGs were retrieved to form a central EEG-database. The EEG-data will be analysed using the ACNS EEG terminology. We designed an electronic case record form (eCRF). Four EEG-specialists from different countries, blinded to patient outcome, will independently classify the EEGs and report through the eCRF. We will describe the prognostic values of pre-specified EEG patterns to predict poor as well as good outcome. We hypothesise three patterns to always be associated with a poor outcome (suppressed background without discharges, suppressed background with continuous periodic discharges and burst-suppression). Inter- and intra-rater variability and whether sedation or level of temperature affects the prognostic values will also be analyzed. Discussion: A well-defined terminology for interpreting post cardiac arrest EEGs is critical for the use of EEG as a prognostic tool. The results of this study may help to validate the ACNS terminology for assessing post cardiac arrest EEGs and identify patterns that could reliably predict outcome.},
  articleno    = {159},
  author       = {Westhall, Erik and Rosén, Ingmar and Rossetti, Andrea O. and van Rootselaar, Anne-Fleur and Kjaer, Troels Wesenberg and Horn, Janneke and Ullen, Susann and Friberg, Hans and Nielsen, Niklas and Cronberg, Tobias},
  issn         = {1471-2377},
  keyword      = {EEG,Prognosis,Interrater variability,Brain injury,Out-of-hospital,cardiac arrest,Hypothermia,Resuscitation},
  language     = {eng},
  publisher    = {BioMed Central},
  series       = {BMC Neurology},
  title        = {Electroencephalography (EEG) for neurological prognostication after cardiac arrest and targeted temperature management; rationale and study design},
  url          = {http://dx.doi.org/10.1186/s12883-014-0159-2},
  volume       = {14},
  year         = {2014},
}