Prognostic value of continuous electroencephalography monitoring in children with severe brain damage.
OBJECTIVE
The purpose of this study is to determine whether there is a relationship between continuous electroencephalography (EEG) monitoring patterns and prognosis for children with severe brain damage. Patients and


METHODS
The different patterns of EEG were analyzed for 103 children (Glasgow Coma Scale [GCS] score < 8) who were monitored with continuous video-EEG (CVEEG) within 72 hours after the onset of coma. The clinical outcomes were scored and evaluated at hospital discharge by the modified Pediatric Cerebral and Overall Performance Category Scale (PCOPCS). EEG parameters of the different prognosis groups were compared and risk factors for prognosis were identified.


RESULTS
Of the 103 children, 36 were in the good prognosis group (PCOPCS scores 1 and 2) and 67 were in the poor prognosis group (PCOPCS scores 3-6). The poor prognosis group had the lower proportion of events in reactive EEG patterns and sleep architecture, and a higher proportion of low-voltage events. Multivariate analyses showed that the lower GCS score and no sleep architecture were significantly associated with poor prognosis.


CONCLUSIONS
Comatose children with higher GCS score and sleep architecture have better clinical outcomes in terms of morbidity and mortality.
Department of Neurology, Children's Hospital of Fudan University, Shanghai, China.
Yan-huai
YH
Lan
Department of Neurology, Children's Hospital of Fudan University, Shanghai, China.
Xiao-mei
XM
Zhu
Department of Neurology, Children's Hospital of Fudan University, Shanghai, China.
Yuan-feng
YF
Zhou
Department of Neurology, Children's Hospital of Fudan University, Shanghai, China.
Peng-ling
PL
Qiu
Department of Intensive Care Unit, Children's Hospital of Fudan University, Shanghai, China.
Guo-ping
GP
Lu
Department of Neurology, Children's Hospital of Fudan University, Shanghai, China.
Dao-kai
DK
Sun
Department of Neurology, Children's Hospital of Fudan University, Shanghai, China.
Yi
Y
Wang
D001930:Brain Injuries / Q000175:diagnosis* / Q000503:physiopathology*; D058256:Brain Waves / Q000502:physiology*; D002648:Child; D002675:Child, Preschool; D004569:Electroencephalography; D005260:Female; D015600:Glasgow Coma Scale; D006801:Humans; D007223:Infant; D008297:Male; D011379:Prognosis; D014741:Video Recording