Abstracts

Rationale: Hypoxic-ischemic encephalopathy (HIE) is one of the leading cause in intensive care units (ICU) patients who show deterioration of consciousness. HIE can occur after cardiopulmonary resuscitation (CPR), asphyxia, low blood and/or cerebral perfusion pressures and hypoxia. It is very important for neurologists to predict neurological outcomes in these patients, but practical guidelines for predicting neurologic outcomes of HIE are still uncertain. This study aimed to establish the prognostic values of HIE based on neurologic examinations, biochemical markers, brain imaging, visual and quantitative analyses of electroencephalography (EEG).

Methods: We have enrolled 198 HIE patients so far with long-term EEG monitoring at Department of Neurology, Ewha Medical Center. The medical history, neurologic examinations including the Glasgow Coma Scale(GCS) motor score, pupillary light reflex, myoclonic seizure, plasma neuron-specific enolase(NSE) level, brain imaging, visual interpretation of EEG and quantitative EEG indices including absolute and relative band powers, and alpha-to-delta ratio were analyzed for neurological outcomes in HIE patients.


Results: Etiologies leading to HIE included cardiac arrest (31.3%), hypotension/hypoxia (due to pulmonary embolism, shock, sepsis, metabolic encephalopathy, drug intoxication)(62.1%), and hanging/drowning/CO intoxication(6.6%). In univariate analysis, GCS motor score≤ 2(p< 0.001), absent light reflex(p< 0.001), myoclonic seizure(p=0.009), serum NSE more than 33μg/L(p< 0.001), extensive cortical involvement in brain imaging(p=0.001), EEG patterns by visual interpretation including background suppression, burst suppression, and generalized periodic epileptiform discharges(p< 0.001) were significantly associated with poor neurologic outcome. EEG index of absolute and relative alpha power and alpha-to-delta ratio were also associated with poor outcome(p=0.003, 0.003, 0.017, respectively). Statistical model based on multivariate analysis has been proposed for prediction of neurological prognostication using combination of these variables.