Neuroprognostication remains a cornerstone of post-cardiac arrest care. Electroencephalography
(EEG), in combination with neurological examination, neuroimaging, and serum biomarkers,
1
is one of the most widely used neuroprognostic tools in this setting. Despite improvements
in the ability to predict outcomes with EEG, further progress is hindered by the variety
of classification systems used, interrater variability,
2
,
3
inconsistent use of established terminology and definitions, confounding effects
of sedative medications, among others. Furthermore, while tools for prediction of
both good and poor outcomes are critically important, efforts have focused more on
honing the identification of poor outcomes with particular attention to optimizing
specificity, to mitigate the downstream consequences of inaccurate predictions of
poor outcome.
4
Accurate identification of individuals who are likely to recover can provide reassurance
to patients’ relatives, inform decisions about escalation of organ support and avoidance
of premature withdrawal of life sustaining therapies.
5
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Article info
Publication history
Published online: December 21, 2022
Accepted:
December 11,
2022
Received:
December 8,
2022
Identification
Copyright
© 2022 Elsevier B.V. All rights reserved.
