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

ObjectiveThis 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 minima...

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Main Authors: Keke Li, Man Li, Wanqing Liu, Yanzhi Wu, Fang Li, Jingwei Xie, Shaolong Zhou, Sen Wang, Yongkun Guo, Jiahui Pan, Xinjun Wang
Format: Article
Language:English
Published: Frontiers Media S.A. 2025-02-01
Series:Frontiers in Human Neuroscience
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Online Access:https://www.frontiersin.org/articles/10.3389/fnhum.2025.1521355/full
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author Keke Li
Man Li
Wanqing Liu
Wanqing Liu
Yanzhi Wu
Fang Li
Jingwei Xie
Jingwei Xie
Jingwei Xie
Shaolong Zhou
Shaolong Zhou
Shaolong Zhou
Sen Wang
Yongkun Guo
Yongkun Guo
Yongkun Guo
Jiahui Pan
Xinjun Wang
Xinjun Wang
Xinjun Wang
Xinjun Wang
author_facet Keke Li
Man Li
Wanqing Liu
Wanqing Liu
Yanzhi Wu
Fang Li
Jingwei Xie
Jingwei Xie
Jingwei Xie
Shaolong Zhou
Shaolong Zhou
Shaolong Zhou
Sen Wang
Yongkun Guo
Yongkun Guo
Yongkun Guo
Jiahui Pan
Xinjun Wang
Xinjun Wang
Xinjun Wang
Xinjun Wang
author_sort Keke Li
collection DOAJ
description ObjectiveThis 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.MethodsA 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.Results1. 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%.ConclusionPolysomnography 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.
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spelling doaj-art-80419f282297449da00cd15aed61c4e02025-08-20T02:13:07ZengFrontiers Media S.A.Frontiers in Human Neuroscience1662-51612025-02-011910.3389/fnhum.2025.15213551521355Electroencephalographic differences between waking and sleeping periods in patients with prolonged disorders of consciousness at different levels of consciousnessKeke Li0Man Li1Wanqing Liu2Wanqing Liu3Yanzhi Wu4Fang Li5Jingwei Xie6Jingwei Xie7Jingwei Xie8Shaolong Zhou9Shaolong Zhou10Shaolong Zhou11Sen Wang12Yongkun Guo13Yongkun Guo14Yongkun Guo15Jiahui Pan16Xinjun Wang17Xinjun Wang18Xinjun Wang19Xinjun Wang20Department of Neurosurgery, The Fifth Affiliated Hospital of Zhengzhou University, Zhengzhou, ChinaSchool of Automation Science and Engineering, South China University of Technology, Guangzhou, ChinaDepartment of Neurosurgery, The Fifth Affiliated Hospital of Zhengzhou University, Zhengzhou, ChinaDepartment of Neurosurgery, The Third Affiliated Hospital of Zhengzhou University, Zhengzhou, ChinaDepartment of Neurosurgery, The Fifth Affiliated Hospital of Zhengzhou University, Zhengzhou, ChinaDepartment of Neurosurgery, The Fifth Affiliated Hospital of Zhengzhou University, Zhengzhou, ChinaDepartment of Neurosurgery, The Fifth Affiliated Hospital of Zhengzhou University, Zhengzhou, ChinaHenan Engineering Research Center for Prevention and Treatment of Brain Injuries, Zhengzhou, ChinaHenan Key Laboratory of Brain Science and Brain Computer Interface Technology, Zhengzhou, ChinaDepartment of Neurosurgery, The Fifth Affiliated Hospital of Zhengzhou University, Zhengzhou, ChinaHenan Engineering Research Center for Prevention and Treatment of Brain Injuries, Zhengzhou, ChinaHenan Key Laboratory of Brain Science and Brain Computer Interface Technology, Zhengzhou, ChinaDepartment of Neurosurgery, The Fifth Affiliated Hospital of Zhengzhou University, Zhengzhou, ChinaDepartment of Neurosurgery, The Fifth Affiliated Hospital of Zhengzhou University, Zhengzhou, ChinaHenan Engineering Research Center for Prevention and Treatment of Brain Injuries, Zhengzhou, ChinaHenan Key Laboratory of Brain Science and Brain Computer Interface Technology, Zhengzhou, ChinaSchool of Software, South China Normal University, Nanhai Software Technology Park, Foshan, Guangdong Province, ChinaDepartment of Neurosurgery, The Fifth Affiliated Hospital of Zhengzhou University, Zhengzhou, ChinaDepartment of Neurosurgery, The Third Affiliated Hospital of Zhengzhou University, Zhengzhou, ChinaHenan Engineering Research Center for Prevention and Treatment of Brain Injuries, Zhengzhou, ChinaHenan Key Laboratory of Brain Science and Brain Computer Interface Technology, Zhengzhou, ChinaObjectiveThis 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.MethodsA 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.Results1. 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%.ConclusionPolysomnography 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.https://www.frontiersin.org/articles/10.3389/fnhum.2025.1521355/fullpolysomnographyprolonged disorders of consciousnessCRS-Rfractal dimensionTeager–Kaiser energy operator
spellingShingle Keke Li
Man Li
Wanqing Liu
Wanqing Liu
Yanzhi Wu
Fang Li
Jingwei Xie
Jingwei Xie
Jingwei Xie
Shaolong Zhou
Shaolong Zhou
Shaolong Zhou
Sen Wang
Yongkun Guo
Yongkun Guo
Yongkun Guo
Jiahui Pan
Xinjun Wang
Xinjun Wang
Xinjun Wang
Xinjun Wang
Electroencephalographic differences between waking and sleeping periods in patients with prolonged disorders of consciousness at different levels of consciousness
Frontiers in Human Neuroscience
polysomnography
prolonged disorders of consciousness
CRS-R
fractal dimension
Teager–Kaiser energy operator
title Electroencephalographic differences between waking and sleeping periods in patients with prolonged disorders of consciousness at different levels of consciousness
title_full Electroencephalographic differences between waking and sleeping periods in patients with prolonged disorders of consciousness at different levels of consciousness
title_fullStr Electroencephalographic differences between waking and sleeping periods in patients with prolonged disorders of consciousness at different levels of consciousness
title_full_unstemmed Electroencephalographic differences between waking and sleeping periods in patients with prolonged disorders of consciousness at different levels of consciousness
title_short Electroencephalographic differences between waking and sleeping periods in patients with prolonged disorders of consciousness at different levels of consciousness
title_sort electroencephalographic differences between waking and sleeping periods in patients with prolonged disorders of consciousness at different levels of consciousness
topic polysomnography
prolonged disorders of consciousness
CRS-R
fractal dimension
Teager–Kaiser energy operator
url https://www.frontiersin.org/articles/10.3389/fnhum.2025.1521355/full
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