Electroencephalogram-Based Complexity Measures as Predictors of Post-operative Neurocognitive Dysfunction.

ABSTRACT: Physiologic signals such as the electroencephalogram (EEG) demonstrate irregular behaviors due to the interaction of multiple control processes operating over different time scales. The complexity of this behavior can be quantified using multi-scale entropy (MSE). High physiologic complexity denotes health, and a loss of complexity can predict adverse outcomes. Since postoperative delirium is particularly hard to predict, we investigated whether the complexity of preoperative and intraoperative frontal EEG signals could predict postoperative delirium and its endophenotype, inattention. To calculate MSE, the sample entropy of EEG recordings was computed at different time scales, then plotted against scale; complexity is the total area under the curve. MSE of frontal EEG recordings was compu

SUBMITTER: Acker L 

PROVIDER: S-EPMC8631543 | biostudies-literature | 2021

REPOSITORIES: biostudies-literature