Literature DB >> 26815669

Prognostic value of various intracranial pathologies in traumatic brain injury.

M M Lesko1, O Bouamra2, S O'Brien3, F Lecky2.   

Abstract

OBJECTIVE: Various intracranial pathologies in traumatic brain injury (TBI) can help to predict patient outcomes. These pathologies can be categorised using the Marshall Classification or the Abbreviated Injury Scale (AIS) dictionary or can be described through traditional descriptive terms such as subarachnoid haemorrhage (SAH), subdural haemorrhage (SDH), epidural haemorrhage (EDH) etc. The purpose of this study is to assess the prognostic value of AIS scores, the Marshall Classification and various intracranial pathologies in TBI.
METHODS: A dataset of 802 TBI patients in the Trauma Audit and Research Network (TARN) database was analysed using logistic regression. First, a baseline model was constructed with age, Glasgow Coma Scale (GCS), pupillary reactivity, cause of injury and presence/absence of extracranial injury as predictors and survival at discharge as the outcome. Subsequently, AIS score, the Marshall Classification and various intracranial pathologies such as haemorrhage, SAH or brain swelling were added in order to assess the relative predictive strength of each variable and also to assess the improvement in the performance of the model.
RESULTS: Various AIS scores or Marshal classes did not appear to significantly affect the outcome. Among traditional descriptive terms, only brain stem injury and brain swelling significantly influenced outcome [odds ratios for survival: 0.17 (95% confidence interval [CI]; 0.08-0.40) and 0.48 (95% CI; 0.29-0.80), respectively]. Neither haemorrhage nor its subtypes, such as SAH, SDH and EDH, were significantly associated with outcome. Adding AIS scores, the Marshall Classification and various intracranial pathologies to the prognostic models resulted in an almost equal increase in the predictive performance of the baseline model.
CONCLUSIONS: In this relatively recent dataset, each of the brain injury classification systems enhanced equally the performance of an early mortality prediction model in traumatic brain injury patients. The significant effect of brain swelling and brain stem injury on the outcome in comparison to injuries such as SAH suggests the need to improve therapeutic approaches to patients who have sustained these injuries.

Entities:  

Keywords:  Computed tomography; Intracranial haemorrhage; Outcome; Traumatic brain injury

Year:  2011        PMID: 26815669     DOI: 10.1007/s00068-011-0167-5

Source DB:  PubMed          Journal:  Eur J Trauma Emerg Surg        ISSN: 1863-9933            Impact factor:   3.693


  23 in total

1.  Predicting outcome after traumatic brain injury: development and validation of a prognostic score based on admission characteristics.

Authors:  Chantal W P M Hukkelhoven; Ewout W Steyerberg; J Dik F Habbema; Elana Farace; Anthony Marmarou; Gordon D Murray; Lawrence F Marshall; Andrew I R Maas
Journal:  J Neurotrauma       Date:  2005-10       Impact factor: 5.269

2.  Prognostic value of the Glasgow Coma Scale and pupil reactivity in traumatic brain injury assessed pre-hospital and on enrollment: an IMPACT analysis.

Authors:  Anthony Marmarou; Juan Lu; Isabella Butcher; Gillian S McHugh; Gordon D Murray; Ewout W Steyerberg; Nino A Mushkudiani; Sung Choi; Andrew I R Maas
Journal:  J Neurotrauma       Date:  2007-02       Impact factor: 5.269

3.  Prognostic value of computerized tomography scan characteristics in traumatic brain injury: results from the IMPACT study.

Authors:  Andrew I R Maas; Ewout W Steyerberg; Isabella Butcher; Ruben Dammers; Juan Lu; Anthony Marmarou; Nino A Mushkudiani; Gillian S McHugh; Gordon D Murray
Journal:  J Neurotrauma       Date:  2007-02       Impact factor: 5.269

4.  Which CT features help predict outcome after head injury?

Authors:  J M Wardlaw; V J Easton; P Statham
Journal:  J Neurol Neurosurg Psychiatry       Date:  2002-02       Impact factor: 10.154

5.  A new approach to outcome prediction in trauma: A comparison with the TRISS model.

Authors:  Omar Bouamra; Alan Wrotchford; Sally Hollis; Andy Vail; Maralyn Woodford; Fiona Lecky
Journal:  J Trauma       Date:  2006-09

6.  Improving the Glasgow Coma Scale score: motor score alone is a better predictor.

Authors:  C Healey; Turner M Osler; Frederick B Rogers; Mark A Healey; Laurent G Glance; Patrick D Kilgo; Steven R Shackford; J Wayne Meredith
Journal:  J Trauma       Date:  2003-04

7.  The Westmead Head Injury Project outcome in severe head injury. A comparative analysis of pre-hospital, clinical and CT variables.

Authors:  M R Fearnside; R J Cook; P McDougall; R J McNeil
Journal:  Br J Neurosurg       Date:  1993       Impact factor: 1.596

8.  Prognosis of traumatic head injury in South Tunisia: a multivariate analysis of 437 cases.

Authors:  Mabrouk Bahloul; Hedi Chelly; Mohamed Ben Hmida; Chokri Ben Hamida; Hichem Ksibi; Hatem Kallel; Adel Chaari; Mondher Kassis; Noureddine Rekik; Mounir Bouaziz
Journal:  J Trauma       Date:  2004-08

9.  Using Abbreviated Injury Scale (AIS) codes to classify Computed Tomography (CT) features in the Marshall System.

Authors:  Mehdi M Lesko; Maralyn Woodford; Laura White; Sarah J O'Brien; Charmaine Childs; Fiona E Lecky
Journal:  BMC Med Res Methodol       Date:  2010-08-06       Impact factor: 4.615

10.  Predicting outcome after traumatic brain injury: development and international validation of prognostic scores based on admission characteristics.

Authors:  Ewout W Steyerberg; Nino Mushkudiani; Pablo Perel; Isabella Butcher; Juan Lu; Gillian S McHugh; Gordon D Murray; Anthony Marmarou; Ian Roberts; J Dik F Habbema; Andrew I R Maas
Journal:  PLoS Med       Date:  2008-08-05       Impact factor: 11.069

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  1 in total

1.  The Risk of Deterioration in GCS13-15 Patients with Traumatic Brain Injury Identified by Computed Tomography Imaging: A Systematic Review and Meta-Analysis.

Authors:  Carl Marincowitz; Fiona E Lecky; William Townend; Aditya Borakati; Andrea Fabbri; Trevor A Sheldon
Journal:  J Neurotrauma       Date:  2018-01-11       Impact factor: 5.269

  1 in total

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