The relation between Glasgow Coma Scale score and later cerebral atrophy in paediatric traumatic brain injury

E.B. Singleton Department of Diagnostic Imaging, Texas Children's Hospital, Houston, TX, USA.
Brain Injury (Impact Factor: 1.81). 04/2009; 23(3):228-33. DOI: 10.1080/02699050802672789
Source: PubMed


To examine initial Glasgow Coma Scale (GCS) score and its relationship with later cerebral atrophy in children with traumatic brain injury (TBI) using Quantitative Magnetic Resonance Imaging (QMRI) at 4 months post-injury. It was hypothesized that a lower GCS score would predict later generalized atrophy. As a guide in assessing paediatric TBI patients, the probability of developing chronic cerebral atrophy was determined based on the initial GCS score.
The probability model used data from 45 paediatric patients (mean age = 13.6) with mild-to-severe TBI and 41 paediatric (mean age = 12.4) orthopaedically-injured children.
This study found a 24% increase in the odds of developing an abnormal ventricle-to-brain ratio (VBR) and a 27% increase in the odds of developing reduced white matter percentage on neuroimaging with each numerical drop in GCS score. Logistic regression models with cut-offs determined by normative QMRI data confirmed that a lower initial GCS score predicts later atrophy.
GCS is a commonly used measure of injury severity. It has proven to be a prognostic indicator of cognitive recovery and functional outcome and is also predictive of later parenchymal change.

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Available from: Alokananda Ghosh, Aug 30, 2015
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    • "Increases in VBR do occur in normal aging that become overtly notable by middle age but sharply increase after age 65. Chronic VBR changes reflective of generalized atrophy in TBI are directly proportional to the severity of injury (Bigler et al., 2006; Wilde et al., 2006a; Ghosh et al., 2009). Likewise, pathological increases in VBR are found in neurodegenerative disorders (Bigler et al., 2004; Carmichael et al., 2007; Olesen et al., 2011). "
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    ABSTRACT: Depending on severity, traumatic brain injury (TBI) induces immediate neuropathological effects that in the mildest form may be transient but as severity increases results in neural damage and degeneration. The first phase of neural degeneration is explainable by the primary acute and secondary neuropathological effects initiated by the injury; however, neuroimaging studies demonstrate a prolonged period of pathological changes that progressively occur even during the chronic phase. This review examines how neuroimaging may be used in TBI to understand (1) the dynamic changes that occur in brain development relevant to understanding the effects of TBI and how these relate to developmental stage when the brain is injured, (2) how TBI interferes with age-typical brain development and the effects of aging thereafter, and (3) how TBI results in greater frontotemporolimbic damage, results in cerebral atrophy, and is more disruptive to white matter neural connectivity. Neuroimaging quantification in TBI demonstrates degenerative effects from brain injury over time. An adverse synergistic influence of TBI with aging may predispose the brain injured individual for the development of neuropsychiatric and neurodegenerative disorders long after surviving the brain injury.
    Frontiers in Human Neuroscience 08/2013; 7:395. DOI:10.3389/fnhum.2013.00395 · 3.63 Impact Factor
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    • "For example, when severity classifi cation is made using the GCS or other similar procedures, some children initially classifi ed as having severe TBI do not demonstrate signifi cant neurocognitive or behavioral defi cits when examined after a period of recovery, and other factors including age at injury and premorbid functioning may account for more variance in neurocognitive outcomes (Fay et al., 2009 ; Lieh-Lai et al., 1992 ; Wells, Minnes, & Phillips, 2009 ). Indeed, the GCS has been described as only a gross predictor of TBI severity and functional outcome (Ghosh et al., 2009 ; Hackbarth et al., 2002 ; Hiekkanen, Kurki, Brandstack, Kairisto, & Tenovuo, 2009 ). Saatman et al. ( 2008 ) also point out that the GCS relies primarily on acute behavioral responses post-injury including best eye, verbal, and motor response, but provides little information about the pathophysiologic mechanisms underlying injury, which may provide additional insights on the nature and severity of the injury. "

    Cluster Analysis in Neuropsychological Research: Recent Applications, Edited by Daniel N. allen, Gerald Goldstein, 01/2013: chapter Classification of Traumatic Brain Injury Severity: A Neuropsychological Approach: pages 95-123; Springer Publishing Company., ISBN: 978-1461467434
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    • "Since experimental models of diffuse TBI cause symmetric bilateral injury to the brain the difference between hemispheres cannot be used to evaluate the tissue loss. Instead, it may be possible to use the ventricle-to-brain ratio which is sometimes used in clinical studies (Anderson et al., 1996; Ghosh et al., 2009). Other measures used to assess cerebral abnormalities in models of brain injury include the Evans index, defined as the maximum distance between the frontal horns divided by the maximum inner diameter of the skull (Evans, 1942; Poca et al., 2005), and cortical thickness (Merkley et al., 2008). "
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    ABSTRACT: All experimental models of traumatic brain injury (TBI) result in a progressive loss of brain tissue. The extent of tissue loss reflects the injury severity and can be measured to evaluate the potential neuroprotective effect of experimental treatments. Quantitation of tissue volumes is commonly performed using evenly spaced brain sections stained using routine histochemical methods and digitally captured. The brain tissue areas are then measured and the corresponding volumes are calculated using the distance between the sections. Measurements of areas are usually performed using a general purpose image analysis software and the results are then transferred to another program for volume calculations. To facilitate the measurement of brain tissue loss we developed novel algorithms which automatically separate the areas of brain tissue from the surrounding image background and identify the ventricles. We implemented these new algorithms by creating a new computer program (SectionToVolume) which also has functions for image organization, image adjustments and volume calculations. We analyzed brain sections from mice subjected to severe focal TBI using both SectionToVolume and ImageJ, a commonly used image analysis program. The volume measurements made by the two programs were highly correlated and analysis using SectionToVolume required considerably less time. The inter-rater reliability was high. Given the extensive use of brain tissue loss measurements in TBI research, SectionToVolume will likely be a useful tool for TBI research. We therefore provide both the source code and the program as attachments to this article.
    Frontiers in Neurology 03/2012; 3:29. DOI:10.3389/fneur.2012.00029
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