Turella, Sara; Dankiewicz, Josef; Friberg, Hans; Jakobsen, Janus Christian; Leithner, Christoph; Levin, Helena; Lilja, Gisela; Moseby-Knappe, Marion; Nielsen, Niklas; Rossetti, Andrea O; Sandroni, Claudio; Zubler, Frédéric; Cronberg, Tobias; Westhall, Erik (2024). The predictive value of highly malignant EEG patterns after cardiac arrest: evaluation of the ERC-ESICM recommendations. Intensive care medicine, 50(1), pp. 90-102. Springer 10.1007/s00134-023-07280-9
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PURPOSE
The 2021 guidelines endorsed by the European Resuscitation Council (ERC) and the European Society of Intensive Care Medicine (ESICM) recommend using highly malignant electroencephalogram (EEG) patterns (HMEP; suppression or burst-suppression) at > 24 h after cardiac arrest (CA) in combination with at least one other concordant predictor to prognosticate poor neurological outcome. We evaluated the prognostic accuracy of HMEP in a large multicentre cohort and investigated the added value of absent EEG reactivity.
METHODS
This is a pre-planned prognostic substudy of the Targeted Temperature Management trial 2. The presence of HMEP and background reactivity to external stimuli on EEG recorded > 24 h after CA was prospectively reported. Poor outcome was measured at 6 months and defined as a modified Rankin Scale score of 4-6. Prognostication was multimodal, and withdrawal of life-sustaining therapy (WLST) was not allowed before 96 h after CA.
RESULTS
845 patients at 59 sites were included. Of these, 579 (69%) had poor outcome, including 304 (36%) with WLST due to poor neurological prognosis. EEG was recorded at a median of 71 h (interquartile range [IQR] 52-93) after CA. HMEP at > 24 h from CA had 50% [95% confidence interval [CI] 46-54] sensitivity and 93% [90-96] specificity to predict poor outcome. Specificity was similar (93%) in 541 patients without WLST. When HMEP were unreactive, specificity improved to 97% [94-99] (p = 0.008).
CONCLUSION
The specificity of the ERC-ESICM-recommended EEG patterns for predicting poor outcome after CA exceeds 90% but is lower than in previous studies, suggesting that large-scale implementation may reduce their accuracy. Combining HMEP with an unreactive EEG background significantly improved specificity. As in other prognostication studies, a self-fulfilling prophecy bias may have contributed to observed results.
Item Type: |
Journal Article (Original Article) |
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Division/Institute: |
04 Faculty of Medicine > Department of Head Organs and Neurology (DKNS) > Clinic of Neurology |
UniBE Contributor: |
Zubler, Frédéric |
Subjects: |
600 Technology > 610 Medicine & health |
ISSN: |
1432-1238 |
Publisher: |
Springer |
Language: |
English |
Submitter: |
Pubmed Import |
Date Deposited: |
05 Jan 2024 12:30 |
Last Modified: |
27 Jan 2024 00:16 |
Publisher DOI: |
10.1007/s00134-023-07280-9 |
PubMed ID: |
38172300 |
Uncontrolled Keywords: |
Brain injury Cardiac arrest Coma EEG Outcome Prognosis |
BORIS DOI: |
10.48350/191250 |
URI: |
https://boris.unibe.ch/id/eprint/191250 |
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