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Early EEG monitoring predicts clinical outcome in patients with moderate to severe traumatic brain injury
There is a need for reliable predictors in patients with moderate to severe traumatic brain injury to assist clinical decision making. We assess the ability of early continuous EEG monitoring at the intensive care unit (ICU) in patients with traumatic brain injury (TBI) to predict long term clinical...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9984683/ https://www.ncbi.nlm.nih.gov/pubmed/36801601 http://dx.doi.org/10.1016/j.nicl.2023.103350 |
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author | Tewarie, Prejaas K.B. Beernink, Tim M.J. Eertman-Meyer, Carin J. Cornet, Alexander D. Beishuizen, Albertus van Putten, Michel J.A.M. Tjepkema-Cloostermans, Marleen C. |
author_facet | Tewarie, Prejaas K.B. Beernink, Tim M.J. Eertman-Meyer, Carin J. Cornet, Alexander D. Beishuizen, Albertus van Putten, Michel J.A.M. Tjepkema-Cloostermans, Marleen C. |
author_sort | Tewarie, Prejaas K.B. |
collection | PubMed |
description | There is a need for reliable predictors in patients with moderate to severe traumatic brain injury to assist clinical decision making. We assess the ability of early continuous EEG monitoring at the intensive care unit (ICU) in patients with traumatic brain injury (TBI) to predict long term clinical outcome and evaluate its complementary value to current clinical standards. We performed continuous EEG measurements in patients with moderate to severe TBI during the first week of ICU admission. We assessed the Extended Glasgow Outcome Scale (GOSE) at 12 months, dichotomized into poor (GOSE 1–3) and good (GOSE 4–8) outcome. We extracted EEG spectral features, brain symmetry index, coherence, aperiodic exponent of the power spectrum, long range temporal correlations, and broken detailed balance. A random forest classifier using feature selection was trained to predict poor clinical outcome based on EEG features at 12, 24, 48, 72 and 96 h after trauma. We compared our predictor with the IMPACT score, the best available predictor, based on clinical, radiological and laboratory findings. In addition we created a combined model using EEG as well as the clinical, radiological and laboratory findings. We included hundred-seven patients. The best prediction model using EEG parameters was found at 72 h after trauma with an AUC of 0.82 (0.69–0.92), specificity of 0.83 (0.67–0.99) and sensitivity of 0.74 (0.63–0.93). The IMPACT score predicted poor outcome with an AUC of 0.81 (0.62–0.93), sensitivity of 0.86 (0.74–0.96) and specificity of 0.70 (0.43–0.83). A model using EEG and clinical, radiological and laboratory parameters resulted in a better prediction of poor outcome (p < 0.001) with an AUC of 0.89 (0.72–0.99), sensitivity of 0.83 (0.62–0.93) and specificity of 0.85 (0.75–1.00). EEG features have potential use for predicting clinical outcome and decision making in patients with moderate to severe TBI and provide complementary information to current clinical standards. |
format | Online Article Text |
id | pubmed-9984683 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Elsevier |
record_format | MEDLINE/PubMed |
spelling | pubmed-99846832023-03-05 Early EEG monitoring predicts clinical outcome in patients with moderate to severe traumatic brain injury Tewarie, Prejaas K.B. Beernink, Tim M.J. Eertman-Meyer, Carin J. Cornet, Alexander D. Beishuizen, Albertus van Putten, Michel J.A.M. Tjepkema-Cloostermans, Marleen C. Neuroimage Clin Regular Article There is a need for reliable predictors in patients with moderate to severe traumatic brain injury to assist clinical decision making. We assess the ability of early continuous EEG monitoring at the intensive care unit (ICU) in patients with traumatic brain injury (TBI) to predict long term clinical outcome and evaluate its complementary value to current clinical standards. We performed continuous EEG measurements in patients with moderate to severe TBI during the first week of ICU admission. We assessed the Extended Glasgow Outcome Scale (GOSE) at 12 months, dichotomized into poor (GOSE 1–3) and good (GOSE 4–8) outcome. We extracted EEG spectral features, brain symmetry index, coherence, aperiodic exponent of the power spectrum, long range temporal correlations, and broken detailed balance. A random forest classifier using feature selection was trained to predict poor clinical outcome based on EEG features at 12, 24, 48, 72 and 96 h after trauma. We compared our predictor with the IMPACT score, the best available predictor, based on clinical, radiological and laboratory findings. In addition we created a combined model using EEG as well as the clinical, radiological and laboratory findings. We included hundred-seven patients. The best prediction model using EEG parameters was found at 72 h after trauma with an AUC of 0.82 (0.69–0.92), specificity of 0.83 (0.67–0.99) and sensitivity of 0.74 (0.63–0.93). The IMPACT score predicted poor outcome with an AUC of 0.81 (0.62–0.93), sensitivity of 0.86 (0.74–0.96) and specificity of 0.70 (0.43–0.83). A model using EEG and clinical, radiological and laboratory parameters resulted in a better prediction of poor outcome (p < 0.001) with an AUC of 0.89 (0.72–0.99), sensitivity of 0.83 (0.62–0.93) and specificity of 0.85 (0.75–1.00). EEG features have potential use for predicting clinical outcome and decision making in patients with moderate to severe TBI and provide complementary information to current clinical standards. Elsevier 2023-02-14 /pmc/articles/PMC9984683/ /pubmed/36801601 http://dx.doi.org/10.1016/j.nicl.2023.103350 Text en © 2023 The Author(s) https://creativecommons.org/licenses/by/4.0/This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Regular Article Tewarie, Prejaas K.B. Beernink, Tim M.J. Eertman-Meyer, Carin J. Cornet, Alexander D. Beishuizen, Albertus van Putten, Michel J.A.M. Tjepkema-Cloostermans, Marleen C. Early EEG monitoring predicts clinical outcome in patients with moderate to severe traumatic brain injury |
title | Early EEG monitoring predicts clinical outcome in patients with moderate to severe traumatic brain injury |
title_full | Early EEG monitoring predicts clinical outcome in patients with moderate to severe traumatic brain injury |
title_fullStr | Early EEG monitoring predicts clinical outcome in patients with moderate to severe traumatic brain injury |
title_full_unstemmed | Early EEG monitoring predicts clinical outcome in patients with moderate to severe traumatic brain injury |
title_short | Early EEG monitoring predicts clinical outcome in patients with moderate to severe traumatic brain injury |
title_sort | early eeg monitoring predicts clinical outcome in patients with moderate to severe traumatic brain injury |
topic | Regular Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9984683/ https://www.ncbi.nlm.nih.gov/pubmed/36801601 http://dx.doi.org/10.1016/j.nicl.2023.103350 |
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