Affiliation:
1. Neurosurgery ICU, Xiangya Hospital, Central South University, Changsha, China
2. General ICU/Department of Critical Care Medicine, Xiangya Hospital, Central South University, Changsha, China
Abstract
Objective This study aimed to explore the effectiveness of quantitative electroencephalogram (EEG) and EEG reactivity (EEG-R) to predict the prognosis of patients with severe traumatic brain injury. Methods This was a prospective observational study on severe traumatic brain injury. Quantitative EEG monitoring was performed for 8 to 12 hours within 14 days of onset. The EEG-R was tested during the monitoring period. We then followed patients for 3 months to determine their level of consciousness. The Glasgow Outcome Scale (GOS) score was used. The score 3, 4, 5 of GOS were defined good prognosis, and score 1 and 2 as poor prognosis. Univariate and multivariate analyses were employed to assess the association of predictors with poor prognosis. Results A total of 56 patients were included in the study. Thirty-two patients (57.1%) awoke (good prognosis) in 3 months after the onset. Twenty-four patients (42.9%) did not awake (poor prognosis), including 11 cases deaths. Univariate analysis showed that Glasgow coma scale (GCS) score, the amplitude-integrated EEG (aEEG), the relative band power (RBP), the relative alpha variability (RAV), the spectral entropy (SE), and EEG-R reached significant difference between the poor-prognosis and good-prognosis groups. However, age, gender, and pupillary light reflex did not correlate significantly with poor prognosis. Furthermore, multivariate logistic regression analysis showed that only RAV and EEG-R were significant independent predictors of poor prognosis, and the prognostic model containing these 2 variables yielded a predictive performance with an area under the curve of 0.882. Conclusions Quantitative EEG and EEG-R may be used to assess the prognosis of patients with severe traumatic brain injury early. RAV and EEG-R were the good predictive indicators of poor prognosis.
Subject
Clinical Neurology,Neurology,General Medicine
Cited by
8 articles.
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