The prognostic value of resting-state EEG in acute post-traumatic unresponsive states
© The Author(s) (2021). Published by Oxford University Press on behalf of the Guarantors of Brain..
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.
| Medienart: |
E-Artikel |
|---|
| Erscheinungsjahr: |
2021 |
|---|---|
| Erschienen: |
2021 |
| Enthalten in: |
Zur Gesamtaufnahme - volume:3 |
|---|---|
| Enthalten in: |
Brain communications - 3(2021), 2 vom: 23., Seite fcab017 |
| Sprache: |
Englisch |
|---|
| Beteiligte Personen: |
O'Donnell, Alice [VerfasserIn] |
|---|
| Links: |
|---|
| Themen: |
|---|
| Anmerkungen: |
Date Revised 11.11.2023 published: Electronic-eCollection Citation Status PubMed-not-MEDLINE |
|---|
| doi: |
10.1093/braincomms/fcab017 |
|---|
| funding: |
|
|---|---|
| Förderinstitution / Projekttitel: |
|
| PPN (Katalog-ID): |
NLM32410099X |
|---|
| LEADER | 01000naa a22002652 4500 | ||
|---|---|---|---|
| 001 | NLM32410099X | ||
| 003 | DE-627 | ||
| 005 | 20231225185611.0 | ||
| 007 | cr uuu---uuuuu | ||
| 008 | 231225s2021 xx |||||o 00| ||eng c | ||
| 024 | 7 | |a 10.1093/braincomms/fcab017 |2 doi | |
| 028 | 5 | 2 | |a pubmed24n1080.xml |
| 035 | |a (DE-627)NLM32410099X | ||
| 035 | |a (NLM)33855295 | ||
| 040 | |a DE-627 |b ger |c DE-627 |e rakwb | ||
| 041 | |a eng | ||
| 100 | 1 | |a O'Donnell, Alice |e verfasserin |4 aut | |
| 245 | 1 | 4 | |a The prognostic value of resting-state EEG in acute post-traumatic unresponsive states |
| 264 | 1 | |c 2021 | |
| 336 | |a Text |b txt |2 rdacontent | ||
| 337 | |a ƒaComputermedien |b c |2 rdamedia | ||
| 338 | |a ƒa Online-Ressource |b cr |2 rdacarrier | ||
| 500 | |a Date Revised 11.11.2023 | ||
| 500 | |a published: Electronic-eCollection | ||
| 500 | |a Citation Status PubMed-not-MEDLINE | ||
| 520 | |a © The Author(s) (2021). Published by Oxford University Press on behalf of the Guarantors of Brain. | ||
| 520 | |a 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 | ||
| 650 | 4 | |a Journal Article | |
| 650 | 4 | |a EEG | |
| 650 | 4 | |a alpha | |
| 650 | 4 | |a coma | |
| 650 | 4 | |a prognosis | |
| 650 | 4 | |a traumatic brain injury | |
| 700 | 1 | |a Pauli, Ruth |e verfasserin |4 aut | |
| 700 | 1 | |a Banellis, Leah |e verfasserin |4 aut | |
| 700 | 1 | |a Sokoliuk, Rodika |e verfasserin |4 aut | |
| 700 | 1 | |a Hayton, Tom |e verfasserin |4 aut | |
| 700 | 1 | |a Sturman, Steve |e verfasserin |4 aut | |
| 700 | 1 | |a Veenith, Tonny |e verfasserin |4 aut | |
| 700 | 1 | |a Yakoub, Kamal M |e verfasserin |4 aut | |
| 700 | 1 | |a Belli, Antonio |e verfasserin |4 aut | |
| 700 | 1 | |a Chennu, Srivas |e verfasserin |4 aut | |
| 700 | 1 | |a Cruse, Damian |e verfasserin |4 aut | |
| 773 | 0 | 8 | |i Enthalten in |t Brain communications |d 2019 |g 3(2021), 2 vom: 23., Seite fcab017 |w (DE-627)NLM302151036 |x 2632-1297 |7 nnns |
| 773 | 1 | 8 | |g volume:3 |g year:2021 |g number:2 |g day:23 |g pages:fcab017 |
| 856 | 4 | 0 | |u http://dx.doi.org/10.1093/braincomms/fcab017 |3 Volltext |
| 912 | |a GBV_USEFLAG_A | ||
| 912 | |a GBV_NLM | ||
| 951 | |a AR | ||
| 952 | |d 3 |j 2021 |e 2 |b 23 |h fcab017 | ||