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Ann Neurol. 2018 May;83(5):958-969. doi: 10.1002/ana.25232. Epub 2018 May 16.

Continuous electroencephalography predicts delayed cerebral ischemia after subarachnoid hemorrhage: A prospective study of diagnostic accuracy.

Author information

1
Division of Neurocritical Care and Emergency Neurology, Massachusetts General Hospital, Boston, MA.
2
Epilepsy Service and Division of Clinical Neurophysiology, Massachusetts General Hospital, Boston, MA.
3
Department of Neurology, Beth Israel Deaconess Medical Center, Boston, MA.
4
Division of Neurocritical Care and Emergency Neurology, Yale-New Haven Hospital, New Haven, CT.
5
Department of Neurology and Rehabilitation Medicine, University of Cincinnati, Cincinnati, OH.
6
Department of Neurology, Comprehensive Epilepsy Center, Free University of Brussels, Erasmus Hospital, Brussels, Belgium.
7
Department of Neurology and Comprehensive Epilepsy Center, Yale University, New Haven, CT.
8
Division of Vascular Neurology, Massachusetts General Hospital, Boston, MA.
9
Department of Neurosurgery, Massachusetts General Hospital, Boston, MA.

Abstract

OBJECTIVE:

Delayed cerebral ischemia (DCI) is a common, disabling complication of subarachnoid hemorrhage (SAH). Preventing DCI is a key focus of neurocritical care, but interventions carry risk and cannot be applied indiscriminately. Although retrospective studies have identified continuous electroencephalographic (cEEG) measures associated with DCI, no study has characterized the accuracy of cEEG with sufficient rigor to justify using it to triage patients to interventions or clinical trials. We therefore prospectively assessed the accuracy of cEEG for predicting DCI, following the Standards for Reporting Diagnostic Accuracy Studies.

METHODS:

We prospectively performed cEEG in nontraumatic, high-grade SAH patients at a single institution. The index test consisted of clinical neurophysiologists prospectively reporting prespecified EEG alarms: (1) decreasing relative alpha variability, (2) decreasing alpha-delta ratio, (3) worsening focal slowing, or (4) late appearing epileptiform abnormalities. The diagnostic reference standard was DCI determined by blinded, adjudicated review. Primary outcome measures were sensitivity and specificity of cEEG for subsequent DCI, determined by multistate survival analysis, adjusted for baseline risk.

RESULTS:

One hundred three of 227 consecutive patients were eligible and underwent cEEG monitoring (7.7-day mean duration). EEG alarms occurred in 96.2% of patients with and 19.6% without subsequent DCI (1.9-day median latency, interquartile range = 0.9-4.1). Among alarm subtypes, late onset epileptiform abnormalities had the highest predictive value. Prespecified EEG findings predicted DCI among patients with low (91% sensitivity, 83% specificity) and high (95% sensitivity, 77% specificity) baseline risk.

INTERPRETATION:

cEEG accurately predicts DCI following SAH and may help target therapies to patients at highest risk of secondary brain injury. Ann Neurol 2018;83:958-969.

PMID:
29659050
PMCID:
PMC6021198
[Available on 2019-05-16]
DOI:
10.1002/ana.25232

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