[Diagnostic value of amplitude-integrated electroencephalography in predicting outcome of newborn patients in neonatal intensive care unit].
OBJECTIVE
To assess the diagnostic value of amplitude-integrated electroencephalography (aEEG) in predicting outcome of newborns who were at high risk for central nervous system without severe hypoxic-ischemic encephalopathy.


METHODS
Forty-two consecutive patients at risks for neurological disorders referred to our level-III NICU were prospectively enrolled in the study over a period of 3 years. They were classified on the basis of their primary diagnoses including hypoglycemic brain damage, meningoencephalitis, bilirubin encephalopathy, and metabolic disease. Clinical data were collected. Amplitude-integrated and raw EEG tracings were assessed for background pattern, sleep-wake cycling, and epileptiform activity. The neuromotor development of survivors was assessed by using the Infant Neurological International Battery (INFANIB).


RESULTS
The characteristic of aEEG tracings in 42 infants showed continuous normal voltage (CNV)(n = 15), discontinuous voltage (DC)(n = 9), burst-suppression (BS) BS(+) (n = 6), BS(-)(n = 7), flat (FT, n = 5); mature sleep-wake cycling (SWC, n = 4), immature SWC (n = 14), no SWC (n = 24); 30 infants (71.4%) had electrical seizures: single seizure (n = 6); repetitive seizures (n = 7), and status epilepticus (SE) (n = 17).aEEG of 20 infants who had poor outcome showed FT (n = 5), BS(-)/SE (n = 6), BS(-)/ repetitive seizures (n = 1) , BS(+)/SE (n = 1), BS(+)/repetitive seizures (n = 1), DC/SE(n = 6). Chi-square analysis and Spearman rank correlation analysis showed the classification of aEEG background pattern, SWC and comprehensive score (score system was developed by evaluation of the above 3 variables) were correlated with the outcome of these infants at high neurological risks.


CONCLUSIONS
Amplitude-integrated electroencephalography can provide important information of the status of cerebral function in neonates at high neurological risk and help to predict their outcome.
Children's Hospital of Zhejiang University School of Medicine, Hangzhou 310003, China.
Fang
F
Luo
Hui-jia
HJ
Lin
Chen-hong
CH
Wang
Yu
Y
Bao
Zheng
Z
Chen
Xiao-lu
XL
Ma
Li-ping
LP
Shi
Li-zhong
LZ
Du
D001921:Brain / Q000502:physiology* / Q000503:physiopathology; D001930:Brain Injuries / Q000175:diagnosis* / Q000209:etiology / Q000503:physiopathology; D004569:Electroencephalography / Q000379:methods*; D004827:Epilepsy / Q000175:diagnosis / Q000209:etiology / Q000503:physiopathology; D006801:Humans; D007003:Hypoglycemia / Q000150:complications; D007231:Infant, Newborn; D007234:Infant, Premature; D007363:Intensive Care Units, Neonatal; D007647:Kernicterus / Q000175:diagnosis / Q000503:physiopathology; D008590:Meningoencephalitis / Q000175:diagnosis* / Q000503:physiopathology; D011237:Predictive Value of Tests; D011379:Prognosis; D012890:Sleep / Q000502:physiology