EEG can Predict Neurologic Outcome in Children Resuscitated from Cardiac Arrest

Yang, Dong Hwa; Ha, Seok Gyun; Kim, Hyo Jeong

Abstract

PURPOSE
Early prediction of prognosis of children resuscitated from cardiac arrest is a major challenge. We investigated the utility of electroencephalography (EEG) and laboratory studies for predicting of neurologic outcome in children resuscitated from cardiac arrest.
METHODS
We retrospectively analyzed medical records of patients who were resuscitated from cardiac arrest from 2006 to 2015 at the Gil Medical Center. Patients aged one month to 18 years were included. EEG analysis included background scoring, reactivity and seizure burden. EEG background was classified score 0 (normal/organized), score 1 (slow and disorganized), score 2 (discontinuous or burst suppression), and score 3 (suppressed and featureless). Neurologic outcome was evaluated by Pediatric Cerebral Performance Category (PCPC) at least 6 months after cardiac arrest.
RESULTS
Total 26 patients were evaluated. Nine patients showed good neurologic outcome (PCPC 1, 2, 3) and 17 patients showed poor neurologic outcome (PCPC 4, 5, 6). Patients of poor neurologic outcome group showed EEG background score 3 in 88.2%, whereas 44.4% in patients of good neurologic outcome group (P=0.028). Electrographic ictal discharges except non-convulsive status epilepticus were presented in 44.4% of good neurologic outcome group and 5.9% of poor neurologic outcome group (P=0.034). Ammonia and lactate levels were higher and pH levels were lower in poor outcome group than good neurologic outcome group.
CONCLUSION
Suppressed and featureless EEG background is associated with poor neurologic outcome and electrographic seizures are associated with good neurologic outcome.