Literature DB >> 17892404

The mayo classification system for traumatic brain injury severity.

James F Malec1, Allen W Brown, Cynthia L Leibson, Julie Testa Flaada, Jayawant N Mandrekar, Nancy N Diehl, Patricia K Perkins.   

Abstract

PURPOSE: To develop a single TBI severity classification system based on commonly used TBI severity measures and indicators that (1) maximally uses available positive evidence to classify TBI severity in three categories: (a) Moderate-Severe (Definite) TBI, (b) Mild (Probable) TBI, (c) Symptomatic (Possible) TBI; (2) reflects current clinical knowledge and relevance; and (3) classifies a larger number of cases than single indicator systems with reasonable accuracy. MAIN
FINDINGS: The study sample of a defined population consisted of 1501 unique Olmsted County residents with at least one confirmed TBI event from 1985 to 1999. Within the sample, 1678 TBI events were confirmed. Single measures of TBI severity were not available in a large percentage of these events, i.e., Glasgow Coma Scale (GCS) was absent in 1242 (74.0%); loss of consciousness, absent in 178 (70.2%), posttraumatic amnesia (PTA), absent in 974 (58.1%), head CT, not done in 827 (49.3%). The Mayo Classification System for TBI Severity was developed to classify cases based on available indicators that included death due to TBI, trauma-related neuroimaging abnormalities, GCS, PTA, loss of consciousness and specified post-concussive symptoms. Using the Mayo system, all cases were classified. For the Moderate-Severe (Definite) TBI classification, estimated sensitivity was 89% and estimated specificity was 98%.
CONCLUSIONS: By maximally using relevant available positive evidence, the Mayo system classifies a larger number of cases than single indicator systems with reasonable accuracy. This system may be of use in retrospective research and for determination of TBI severity for planning postacute clinical care.

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Year:  2007        PMID: 17892404     DOI: 10.1089/neu.2006.0245

Source DB:  PubMed          Journal:  J Neurotrauma        ISSN: 0897-7151            Impact factor:   5.269


  143 in total

1.  Comparison of SNOMED CT versus Medcin terminology concept coverage for mild Traumatic Brain Injury.

Authors:  Diane Montella; Steven H Brown; Peter L Elkin; James C Jackson; S Trent Rosenbloom; Dietlind Wahner-Roedler; Gail Welsh; Bryan Cotton; Oscar D Guillamondegui; Henry Lew; Katherine H Taber; Larry A Tupler; Rodney Vanderploeg; Theodore Speroff
Journal:  AMIA Annu Symp Proc       Date:  2011-10-22

2.  Medical care costs associated with traumatic brain injury over the full spectrum of disease: a controlled population-based study.

Authors:  Cynthia L Leibson; Allen W Brown; Kirsten Hall Long; Jeanine E Ransom; Jay Mandrekar; Turner M Osler; James F Malec
Journal:  J Neurotrauma       Date:  2012-04-26       Impact factor: 5.269

3.  Incidence of traumatic brain injury across the full disease spectrum: a population-based medical record review study.

Authors:  Cynthia L Leibson; Allen W Brown; Jeanine E Ransom; Nancy N Diehl; Patricia K Perkins; Jay Mandrekar; James F Malec
Journal:  Epidemiology       Date:  2011-11       Impact factor: 4.822

4.  Disturbed cortico-subcortical interactions during motor task switching in traumatic brain injury.

Authors:  Inge Leunissen; James P Coxon; Monique Geurts; Karen Caeyenberghs; Karla Michiels; Stefan Sunaert; Stephan P Swinnen
Journal:  Hum Brain Mapp       Date:  2012-01-30       Impact factor: 5.038

5.  Parent-Child Interactions During the Initial Weeks Following Brain Injury in Young Children.

Authors:  Shari L Wade; H Gerry Taylor; Nicolay Chertkoff Walz; Shelia Salisbury; Terry Stancin; Lori A Bernard; Karen Oberjohn; Keith Owen Yeates
Journal:  Rehabil Psychol       Date:  2008-05

6.  Convergent thinking and traumatic brain injury: an investigation of performance on the remote associate test.

Authors:  Arianna Rigon; Justin Reber; Nirav N Patel; Melissa C Duff
Journal:  Brain Inj       Date:  2018-06-08       Impact factor: 2.311

7.  Computational modelling of traumatic brain injury predicts the location of chronic traumatic encephalopathy pathology.

Authors:  Mazdak Ghajari; Peter J Hellyer; David J Sharp
Journal:  Brain       Date:  2017-01-02       Impact factor: 13.501

8.  Long-term survival after traumatic brain injury: a population-based analysis controlled for nonhead trauma.

Authors:  Allen W Brown; Cynthia L Leibson; Jay Mandrekar; Jeanine E Ransom; James F Malec
Journal:  J Head Trauma Rehabil       Date:  2014 Jan-Feb       Impact factor: 2.710

9.  Longitudinal Metabolite Changes after Traumatic Brain Injury: A Prospective Pediatric Magnetic Resonance Spectroscopic Imaging Study.

Authors:  Barbara Holshouser; Jamie Pivonka-Jones; Joy G Nichols; Udo Oyoyo; Karen Tong; Nirmalya Ghosh; Stephen Ashwal
Journal:  J Neurotrauma       Date:  2018-12-20       Impact factor: 5.269

10.  White matter correlates of different aspects of facial affect recognition impairment following traumatic brain injury.

Authors:  Arianna Rigon; Michelle W Voss; Lyn S Turkstra; Bilge Mutlu; Melissa C Duff
Journal:  Soc Neurosci       Date:  2018-06-28       Impact factor: 2.083

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