| Abstrakt: |
A recent study conducted by Semmelweis University in Budapest, Hungary, explored the use of electroencephalography (EEG) connectivity and network analyses in predicting outcomes for patients with disorders of consciousness (DOC). The researchers found that EEG connectivity and network metrics had a higher accuracy in predicting outcomes compared to the widely used clinical scale, Coma Recovery Scale-Revised (CRS-R). Additionally, EEG spectral power was found to be comparable to EEG connectivity and graph-theory measures in prognostic capacity. The study suggests that multivariate automated outcome prediction tools may outperform clinical and EEG markers. [Extracted from the article] |
