• Shavonne L Massey, Nicholas S Abend, J William Gaynor, Daniel J Licht, Vinay M Nadkarni, Alexis A Topjian, Rui Xiao, and Maryam Y Naim.
• Division of Neurology, Departments of Neurology and Pediatrics, Children's Hospital of Philadelphia, University of Pennsylvania School of Medicine, 3501 Civic Center Boulevard, Philadelphia, PA, USA. Electronic address: masseysl@email.chop.edu.
• Resuscitation. 2019 Nov 1; 144: 67-74.

AimTo identify EEG changes that could predict impending cardiac arrest (CA) in neonates with congenital heart disease undergoing postoperative continuous EEG monitoring.MethodsSingle-center observational study of neonates who underwent cardiac surgery and had CA postoperatively while undergoing EEG monitoring from 2012-2018. Clinical data were extracted from the medical record. EEG backgrounds were evaluated at defined time-points using standardized terminology.ResultsWe assessed 22 neonates. The median gestational age was 38.7 weeks (IQR 37.6, 39), the median age at surgery was 5 days (IQR 2, 8), 12 patients (55%) underwent repair for hypoplastic left heart syndrome, and the median time from cardiac intensive care unit arrival postoperatively to CA was 9.5 h (IQR 7, 23). The initial EEG background was abnormal in 15 (68%). All 22 neonates (100%) had worsening of the EEG background prior to initiation of chest compressions for CA at a median of 3 min (IQR 1.5, 3). Eighteen neonates (82%) had an EEG change more than 1 min prior to chest compressions. The EEG backgrounds immediately prior to CA were continuous low voltage in 1 (5%), excessive discontinuity in 8 (36%), burst-suppression in 2 (9%), and low voltage suppression in 11 (50%).ConclusionEEG background was abnormal in 68% of neonates at EEG monitoring onset and worsened in all minutes before CA. EEG background changes may be an early sign of impending CA and indicative of developing cerebral dysfunction. Further study is needed to determine whether rapid identification of EEG changes could drive implementation of interventions to prevent CA.Copyright © 2019 Elsevier B.V. All rights reserved.

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