Electroencephalographic differences between waking and sleeping periods in patients with prolonged disorders of consciousness at different levels of consciousness.

Objective: This study aimed to explore differences in sleep electroencephalogram (EEG) patterns in individuals with prolonged disorders of consciousness, utilizing polysomnography (PSG) to assist in distinguishing between the vegetative state (VS)/unresponsive wakefulness syndrome (UWS) and the minimally conscious state (MCS), thereby reducing misdiagnosis rates and enhancing the quality of medical treatment.

Methods: A total of 40 patients with prolonged disorders of consciousness (pDOC; 27 patients in the VS/UWS and 13 in the MCS) underwent polysomnography. We analyzed differential EEG indices between VS/UWS and MCS groups and performed correlation analyses between these indices and the Coma Recovery Scale-Revised (CRS-R) scores. The diagnostic accuracy of the differential indices was evaluated using receiver operating characteristic (ROC) curves.

Results: 1. The fractal dimension (Higuchi's fractal dimension (HFD)) of patients in the MCS tended to be higher than that of patients in the VS/UWS across all phases, with a significant difference only in the waking phase (p < 0.05). The HFD in the waking phase was positively correlated with the CRS-R score and exhibited the highest diagnostic accuracy at 88.3%. The Teager-Kaiser energy operator (TKEO) also showed higher levels in patients in the MCS compared to those in the VS/UWS, significantly so in the NREM2 phase (p < 0.05), with a positive correlation with the CRS-R score and diagnostic accuracy of 75.2%. The δ-band power spectral density [PSD(δ)] in the patients in the MCS was lower than that in those in the VS/UWS, significantly so in the waking phase (p < 0.05), and it was negatively correlated with the CRS-R score, with diagnostic accuracy of 71.5%.

Conclusion: Polysomnography for the VS/UWS and MCS revealed significant differences, aiding in distinguishing between the two patient categories and reducing misdiagnosis rates. Notably, the HFD and PSD(δ) showed significantly better performance during wakefulness compared to sleep, while the TKEO was more prominent in the NREM2 stage. Notably, the HFD exhibited a robust correlation with the CRS-R scores, the highest diagnostic accuracy, and immense promise in the clinical diagnosis of prolonged disorders of consciousness.