Beside Resting-State EEG in the Diagnosis and Prognosis of Patients with Disorders of Consciousness

Background/Objectives: Behavioral scales are the primary diagnostic tool for disorders of consciousness (DOC) but carry a high risk of misdiagnosis. Bedside resting-state EEG (rs-EEG) enables non-invasive objective brain function evaluation, although its diagnostic and prognostic value for DOC remains understudied. Methods: This study enrolled 207 DOC patients with guardian-signed informed consent. Weekly bedside 4-channel rs-EEG and CRS-R behavioral assessments were conducted during hospitalization. We systematically compared three categories of EEG metrics: nonlinear entropies (PE, SamEn), phase coupling parameters, and functional connectivity indices (SI, wPLI), evaluating their ability to stratify consciousness and forecast outcomes. Results: Permutation entropy (PE) stood out with triple functions: cross-sectional consciousness grading, longitudinal dynamic tracking, and prognosis prediction, surpassing all other EEG features. SamEn merely discriminates VS/UWS from MCS/EMCS but fails to separate MCS and EMCS. Power spectra, phase coupling, SI, and wPLI only yield group discrepancies at limited leads or frequency bands with unstable stratification, acting merely as auxiliary markers. Subtype-specific prognostic signatures were identified: frontal β-wPLI and parietal PE predict consciousness recovery in VS/UWS, whereas fronto-parietal α-wPLI predicts improvement in MCS patients. Conclusions: The bedside rs-EEG reliably assesses consciousness and predicts DOC outcomes, and PE possesses prominent clinical value for DOC diagnosis and prognostic stratification.