Early EEG contributes to multimodal outcome prediction of XXXX .

@entity1 @entity158 @entity772 @entity1167
OBJECTIVES: Early identification of potential recovery of @entity772 is a major challenge. We studied the additional predictive value of EEG. METHODS: Two hundred seventy-seven consecutive @entity772 @entity1 after @entity1167 were included in a prospective cohort study on 2 intensive care units. Continuous EEG was measured during the first 3 days. EEGs were classified as unfavorable (isoelectric, low-voltage, burst-suppression with identical bursts), intermediate, or favorable (continuous patterns), at 12, 24, 48, and 72 hours. Outcome was dichotomized as good or poor. Resuscitation, demographic, clinical, somatosensory evoked potential, and EEG measures were related to outcome at 6 months using logistic regression analysis. Analyses of diagnostic accuracy included receiver operating characteristics and calculation of predictive values. RESULTS: Poor outcome occurred in 149 @entity1 (54%). Single measures unequivocally predicting poor outcome were an unfavorable EEG pattern at 24 hours, absent pupillary light responses at 48 hours, and absent somatosensory evoked potentials at 72 hours. Together, these had a specificity of 100% and a sensitivity of 50%. For the remaining 203 @entity1 , who were still in the "gray zone" at 72 hours, a predictive model including unfavorable EEG patterns at 12 hours, absent or extensor motor response to @entity158 at 72 hours, and higher age had an area under the curve of 0.90 (95% confidence interval 0.84-0.96). Favorable EEG patterns at 12 hours were strongly associated with good outcome. EEG beyond 24 hours had no additional predictive value. CONCLUSIONS: EEG within 24 hours is a robust contributor to prediction of poor or good outcome of @entity772 @entity1 after @entity1167 .
