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The Characteristics of Electroencephalogram Signatures in Minimally Conscious State Patients Induced by General Anesthesia
- Source :
- IEEE Transactions on Biomedical Engineering; November 2023, Vol. 70 Issue: 11 p3239-3247, 9p
- Publication Year :
- 2023
-
Abstract
- Objective: General anesthesia (GA) is necessary for surgery, even for patients in a minimally conscious state (MCS). The characteristics of the electroencephalogram (EEG) signatures of the MCS patients under GA are still unclear. Methods: The EEG during GA were recorded from 10 MCS patients undergoing spinal cord stimulation surgery. The power spectrum, phase-amplitude coupling (PAC), the diversity of connectivity, and the functional network were investigated. Long term recovery was assessed by the Coma Recovery Scale-Revised at one year after the surgery, and the characteristics of the patients with good or bad prognosis status were compared. Results: For the four MCS patients with good prognostic recovery, slow oscillation (0.1–1 Hz) and the alpha band (8–12 Hz) in the frontal areas increased during the maintenance of a surgical state of anesthesia (MOSSA), and “peak-max” and “trough-max” patterns emerged in frontal and parietal areas. During MOSSA, the six MCS patients with bad prognosis demonstrated: increased modulation index, reduced diversity of connectivity (from mean±SD of 0.877 ± 0.003 to 0.776 ± 0.003, p < 0.001), reduced function connectivity significantly in theta band (from mean±SD of 1.032 ± 0.043 to 0.589 ± 0.036, p < 0.001, in prefrontal-frontal; and from mean±SD of 0.989 ± 0.043 to 0.684 ± 0.036, p < 0.001, in frontal-parietal) and reduced local and global efficiency of the network in delta band. Conclusions: A bad prognosis in MCS patients is associated with signs of impaired thalamocortical and cortico-cortical connectivity – as indicated by inability to produce inter-frequency coupling and phase synchronization. These indices may have a role in predicting the long-term recovery of MCS patients.
Details
- Language :
- English
- ISSN :
- 00189294
- Volume :
- 70
- Issue :
- 11
- Database :
- Supplemental Index
- Journal :
- IEEE Transactions on Biomedical Engineering
- Publication Type :
- Periodical
- Accession number :
- ejs64349217
- Full Text :
- https://doi.org/10.1109/TBME.2023.3287203