The prognostic value of resting-state EEG in acute post-traumatic unresponsive states.

Autor:	O'Donnell A; Birmingham Medical School, University of Birmingham, Edgbaston B15 2TT, UK.; Centre for Human Brain Health, University of Birmingham, Edgbaston B15 2TT, UK.; School of Psychology, University of Birmingham, Edgbaston B15 2TT, UK., Pauli R; Centre for Human Brain Health, University of Birmingham, Edgbaston B15 2TT, UK.; School of Psychology, University of Birmingham, Edgbaston B15 2TT, UK., Banellis L; Centre for Human Brain Health, University of Birmingham, Edgbaston B15 2TT, UK.; School of Psychology, University of Birmingham, Edgbaston B15 2TT, UK., Sokoliuk R; Centre for Human Brain Health, University of Birmingham, Edgbaston B15 2TT, UK.; School of Psychology, University of Birmingham, Edgbaston B15 2TT, UK., Hayton T; National Institute for Health Research Surgical Reconstruction and Microbiology Research Centre, Birmingham B15 2TH, UK., Sturman S; National Institute for Health Research Surgical Reconstruction and Microbiology Research Centre, Birmingham B15 2TH, UK., Veenith T; National Institute for Health Research Surgical Reconstruction and Microbiology Research Centre, Birmingham B15 2TH, UK.; Birmingham Acute Care Research Group, Institute of Inflammation and Ageing, University of Birmingham, Edgbaston B15 2TT, UK., Yakoub KM; National Institute for Health Research Surgical Reconstruction and Microbiology Research Centre, Birmingham B15 2TH, UK., Belli A; National Institute for Health Research Surgical Reconstruction and Microbiology Research Centre, Birmingham B15 2TH, UK., Chennu S; School of Computing, University of Kent, Canterbury CT2 7NZ, UK., Cruse D; Centre for Human Brain Health, University of Birmingham, Edgbaston B15 2TT, UK.; School of Psychology, University of Birmingham, Edgbaston B15 2TT, UK.
Jazyk:	angličtina
Zdroj:	Brain communications [Brain Commun] 2021 Mar 17; Vol. 3 (2), pp. fcab017. Date of Electronic Publication: 2021 Mar 17 (Print Publication: 2021).
DOI:	10.1093/braincomms/fcab017
Abstrakt:	Accurate early prognostication is vital for appropriate long-term care decisions after traumatic brain injury. While measures of resting-state EEG oscillations and their network properties, derived from graph theory, have been shown to provide clinically useful information regarding diagnosis and recovery in patients with chronic disorders of consciousness, little is known about the value of these network measures when calculated from a standard clinical low-density EEG in the acute phase post-injury. To investigate this link, we first validated a set of measures of oscillatory network features between high-density and low-density resting-state EEG in healthy individuals, thus ensuring accurate estimation of underlying cortical function in clinical recordings from patients. Next, we investigated the relationship between these features and the clinical picture and outcome of a group of 18 patients in acute post-traumatic unresponsive states who were not following commands 2 days+ after sedation hold. While the complexity of the alpha network, as indexed by the standard deviation of the participation coefficients, was significantly related to the patients' clinical picture at the time of EEG, no network features were significantly related to outcome at 3 or 6 months post-injury. Rather, mean relative alpha power across all electrodes improved the accuracy of outcome prediction at 3 months relative to clinical features alone. These results highlight the link between the alpha rhythm and clinical signs of consciousness and suggest the potential for simple measures of resting-state EEG band power to provide a coarse snapshot of brain health for stratification of patients for rehabilitation, therapy and assessments of both covert and overt cognition. (© The Author(s) (2021). Published by Oxford University Press on behalf of the Guarantors of Brain.)
Databáze:	MEDLINE
Externí odkaz:	Zobrazit plný text záznamu