2016
DOI: 10.1016/j.clinph.2016.04.008
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Single electroencephalographic patterns as specific and time-dependent indicators of good and poor outcome after cardiac arrest

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Cited by 67 publications
(65 citation statements)
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“…Measurement of EEG and SEP was performed according to protocols published by Spalletti et al 21 and Scarpino et al, 26 respectively. In this study, we have only reported information concerning the classification of patients according to these neurophysiological tests.…”
Section: Neurophysiological Assessmentmentioning
confidence: 99%
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“…Measurement of EEG and SEP was performed according to protocols published by Spalletti et al 21 and Scarpino et al, 26 respectively. In this study, we have only reported information concerning the classification of patients according to these neurophysiological tests.…”
Section: Neurophysiological Assessmentmentioning
confidence: 99%
“…7 However, this predictor has low sensitivity; in fact, no more than 40% of all CA patients show this SEP pattern. [16][17][18][19][20][21] Nevertheless, the relationship between SEPs and EEG patterns is still poorly understood. However, these studies have some limitations, mainly concerning the use of different methods to evaluate cortical SEP amplitude, which limits the comparison of results between studies.…”
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confidence: 99%
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“…In all studies on early EEG for prognostication after cardiac arrest, a continuous, normal amplitude background pattern at 12 hours was associated with a good neurological outcome . Otherwise, isoelectric or low‐voltage patterns at 24 hours after cardiac arrest were invariably associated with poor outcome .…”
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confidence: 99%
“…The best discrimination between patients with good and poor outcomes was possible with EEG recorded within the first 24 hours after cardiac arrest, despite treatment with targeted temperature management and sedation . The prognostic value of the EEG seemed lower after the first 24 hours and remained unclear for the period beyond 72 hours . Several previous studies did not explicitly acknowledge the time dependency of postanoxic EEG patterns …”
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confidence: 99%