Neurophysiological and neuroradiological multimodal approach for early poor outcome prediction after cardiac arrest

Introduction: Prognosticating outcome after cardiac arrest(CA) requires a multimodal approach. However, evidence regarding combinations of methods is limited. We evaluated whether the combination of electroencephalography( EEG), somatosensory evoked potentials(SEPs) and brain computed tomography(CT) could predict poor outcome. Methods: We screened our database regarding patients successfully resuscitated after CA, for whom EEG, SEPs and brain CT were available within 24 h. EEG patterns were classified according to American Clinical Neurophysiological Society terminology; SEPs were graded accounting for the cortical responses of each hemisphere; and the grey matter/white matter(GM/WM) ratio was evaluated by brain CT. EEG patterns, SEP findings and GM/WM ratio (with a specificity of 100%) were, individually and in combination, related to poor outcome (death/unresponsive wakefulness state) at 6-month follow-up, using the cerebral performance categories(CPC). Results: EEG, SEPs and brain CT were available in 183/273(67%) patients. Bilateral absent/absent-pathologic (AA/AP) cortical SEPs predicted a poor outcome with a sensitivity of 58.5%. A GM/WM ratio < 1.21 predicted a poor outcome with a sensitivity of 50.4%. Isoelectric/burst-suppression EEG patterns predicted a poor outcome with a sensitivity of 43%. If at least one of these poor prognostic patterns was present, sensitivity for an ominous outcome increased to 71.5%. If, in the same subject, two poor prognostic patterns were simultaneously present, sensitivity was 48%. If all three poor prognostic patterns were present, sensitivity decreased by up to 23%. Conclusion: In this population, in which life-sustaining treatments were never suspended, the combination of EEG, SEPs and brain CT improved the sensitivity, maintaining the specificity of poor outcome prediction.