Literature DB >> 11207333

An EEG severity index of traumatic brain injury.

R W Thatcher1, D M North, R T Curtin, R A Walker, C J Biver, J F Gomez, A M Salazar.   

Abstract

EEG spectral analyses were conducted from 19 scalp locations for patients with mild (n=40), moderate (n=25), and severe (n=43) traumatic brain injury (TBI), 15 days to 4 years after injury. Severity of TBI was judged by emergency hospital admission records (Glasgow Coma Score and duration of coma and amnesia). Highest-loading EEG variables on each factor that differed significantly between severe and mild TBI by univariate t-test were entered into a multivariate discriminant analysis, yielding 16 variables. Discriminant analysis between mild and severe TBI groups showed classification accuracy of 96.39%, sensitivity 95.45%, and specificity 97.44%. The EEG discriminant score also measured intermediate severity in moderate TBI patients. Results were cross-validated in 503 VA patients. Significant correlations between EEG discriminant scores, emergency admission measures, and post-trauma neuropsychological test scores validated the discriminant function as an index of severity of injury and a classifier of the extremes of severity.

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Year:  2001        PMID: 11207333     DOI: 10.1176/jnp.13.1.77

Source DB:  PubMed          Journal:  J Neuropsychiatry Clin Neurosci        ISSN: 0895-0172            Impact factor:   2.198


  27 in total

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Review 2.  A Review of the Effectiveness of Neuroimaging Modalities for the Detection of Traumatic Brain Injury.

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Review 4.  Electroencephalography and quantitative electroencephalography in mild traumatic brain injury.

Authors:  Zulfi Haneef; Harvey S Levin; James D Frost; Eli M Mizrahi
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5.  The Patient Repository for EEG Data + Computational Tools (PRED+CT).

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7.  Reductions in qEEG slowing over 1 year and after treatment with Cerebrolysin in patients with moderate-severe traumatic brain injury.

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8.  Identification of hematomas in mild traumatic brain injury using an index of quantitative brain electrical activity.

Authors:  Leslie S Prichep; Rosanne Naunheim; Jeffrey Bazarian; W Andrew Mould; Daniel Hanley
Journal:  J Neurotrauma       Date:  2015-01-01       Impact factor: 5.269

9.  Callosal dysfunction explains injury sequelae in a computational network model of axonal injury.

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Journal:  J Neurophysiol       Date:  2016-09-28       Impact factor: 2.714

10.  Dejian mind-body intervention improves the functioning of a patient with chronic epilepsy: a case report.

Authors:  Agnes S Chan; Sophia L Sze; Mei-Chun Cheung; Joseph Mk Lam; Dejian Shi
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