Early EEG Features for Outcome Prediction After Cardiac Arrest in Children.

ABSTRACT:

Purpose

We aimed to determine which early EEG features and feature combinations most accurately predicted short-term neurobehavioral outcomes and survival in children resuscitated after cardiac arrest.

Methods

This was a prospective, single-center observational study of infants and children resuscitated from cardiac arrest who underwent conventional EEG monitoring with standardized EEG scoring. Logistic regression evaluated the marginal effect of each EEG variable or EEG variable combinations on the outcome. The primary outcome was neurobehavioral outcome (Pediatric Cerebral Performance Category score), and the secondary outcome was mortality. The authors identified the models with the highest areas under the receiver operating characteristic curve (AUC), evaluated the optim

SUBMITTER: Fung FW 

PROVIDER: S-EPMC6731130 | biostudies-literature | 2019 Sep

REPOSITORIES: biostudies-literature