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Dataset Information

Predicting early recovery of consciousness after cardiac arrest supported by quantitative electroencephalography.


ABSTRACT:

Objective

To determine the ability of quantitative electroencephalography (QEEG) to improve the accuracy of predicting recovery of consciousness by post-cardiac arrest day 10.

Methods

Unconscious survivors of cardiac arrest undergoing daily clinical and EEG assessments through post-cardiac arrest day 10 were studied in a prospective observational cohort study. Power spectral density, local coherence, and permutation entropy were calculated from daily EEG clips following a painful stimulus. Recovery of consciousness was defined as following at least simple commands by day 10. We determined the impact of EEG metrics to predict recovery when analyzed with established predictors of recovery using partial least squares regression models. Explained variance analysis identified whi

SUBMITTER: Bauerschmidt A 

PROVIDER: S-EPMC10008439 | biostudies-literature | 2021 Aug

REPOSITORIES: biostudies-literature