Publication: Electroencephalographic reactivity as predictor of neurological outcome in postanoxic coma: A multicenter prospective cohort study
Issued Date
2019-07-01
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ISSN
15318249
03645134
03645134
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2-s2.0-85067228743
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Mahidol University
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SCOPUS
Bibliographic Citation
Annals of Neurology. Vol.86, No.1 (2019), 17-27
Suggested Citation
Marjolein M. Admiraal, Anne Fleur van Rootselaar, Jeannette Hofmeijer, Cornelia W.E. Hoedemaekers, Christiaan R. van Kaam, Hanneke M. Keijzer, Michel J.A.M. van Putten, Marcus J. Schultz, Janneke Horn Electroencephalographic reactivity as predictor of neurological outcome in postanoxic coma: A multicenter prospective cohort study. Annals of Neurology. Vol.86, No.1 (2019), 17-27. doi:10.1002/ana.25507 Retrieved from: https://repository.li.mahidol.ac.th/handle/20.500.14594/51582
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Title
Electroencephalographic reactivity as predictor of neurological outcome in postanoxic coma: A multicenter prospective cohort study
Abstract
© 2019 The Authors. Annals of Neurology published by Wiley Periodicals, Inc. on behalf of American Neurological Association. Objective: Outcome prediction in patients after cardiac arrest (CA) is challenging. Electroencephalographic reactivity (EEG-R) might be a reliable predictor. We aimed to determine the prognostic value of EEG-R using a standardized assessment. Methods: In a prospective cohort study, a strictly defined EEG-R assessment protocol was executed twice per day in adult patients after CA. EEG-R was classified as present or absent by 3 EEG readers, blinded to patient characteristics. Uncertain reactivity was classified as present. Primary outcome was best Cerebral Performance Category score (CPC) in 6 months after CA, dichotomized as good (CPC = 1–2) or poor (CPC = 3–5). EEG-R was considered reliable for predicting poor outcome if specificity was ≥95%. For good outcome prediction, a specificity of ≥80% was used. Added value of EEG-R was the increase in specificity when combined with EEG background, neurological examination, and somatosensory evoked potentials (SSEPs). Results: Of 160 patients enrolled, 149 were available for analyses. Absence of EEG-R for poor outcome prediction had a specificity of 82% and a sensitivity of 73%. For good outcome prediction, specificity was 73% and sensitivity 82%. Specificity for poor outcome prediction increased from 98% to 99% when EEG-R was added to a multimodal model. For good outcome prediction, specificity increased from 70% to 89%. Interpretation: EEG-R testing in itself is not sufficiently reliable for outcome prediction in patients after CA. For poor outcome prediction, it has no substantial added value to EEG background, neurological examination, and SSEPs. For prediction of good outcome, EEG-R seems to have added value. ANN NEUROL 2019.