Literature DB >> 22994879

Multivariate outcome prediction in traumatic brain injury with focus on laboratory values.

David W Nelson1, Anders Rudehill, Robert M MacCallum, Anders Holst, Michael Wanecek, Eddie Weitzberg, Bo-Michael Bellander.   

Abstract

Traumatic brain injury (TBI) is a major cause of morbidity and mortality. Identifying factors relevant to outcome can provide a better understanding of TBI pathophysiology, in addition to aiding prognostication. Many common laboratory variables have been related to outcome but may not be independent predictors in a multivariate setting. In this study, 757 patients were identified in the Karolinska TBI database who had retrievable early laboratory variables. These were analyzed towards a dichotomized Glasgow Outcome Scale (GOS) with logistic regression and relevance vector machines, a non-linear machine learning method, univariately and controlled for the known important predictors in TBI outcome: age, Glasgow Coma Score (GCS), pupil response, and computed tomography (CT) score. Accuracy was assessed with Nagelkerke's pseudo R². Of the 18 investigated laboratory variables, 15 were found significant (p<0.05) towards outcome in univariate analyses. In contrast, when adjusting for other predictors, few remained significant. Creatinine was found an independent predictor of TBI outcome. Glucose, albumin, and osmolarity levels were also identified as predictors, depending on analysis method. A worse outcome related to increasing osmolarity may warrant further study. Importantly, hemoglobin was not found significant when adjusted for post-resuscitation GCS as opposed to an admission GCS, and timing of GCS can thus have a major impact on conclusions. In total, laboratory variables added an additional 1.3-4.4% to pseudo R².

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Year:  2012        PMID: 22994879     DOI: 10.1089/neu.2012.2468

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


  6 in total

1.  Predicting long-term outcome after traumatic brain injury using repeated measurements of Glasgow Coma Scale and data mining methods.

Authors:  Hsueh-Yi Lu; Tzu-Chi Li; Yong-Kwang Tu; Jui-Chang Tsai; Hong-Shiee Lai; Lu-Ting Kuo
Journal:  J Med Syst       Date:  2015-01-31       Impact factor: 4.460

2.  Genetic Variation in the Vesicular Monoamine Transporter: Preliminary Associations With Cognitive Outcomes After Severe Traumatic Brain Injury.

Authors:  Steven M Markos; Michelle D Failla; Anne C Ritter; C Edward Dixon; Yvette P Conley; Joseph H Ricker; Patricia M Arenth; Shannon B Juengst; Amy K Wagner
Journal:  J Head Trauma Rehabil       Date:  2017 Mar/Apr       Impact factor: 2.710

3.  The Value of Artificial Intelligence in Laboratory Medicine.

Authors:  Ketan Paranjape; Michiel Schinkel; Richard D Hammer; Bo Schouten; R S Nannan Panday; Paul W G Elbers; Mark H H Kramer; Prabath Nanayakkara
Journal:  Am J Clin Pathol       Date:  2021-05-18       Impact factor: 2.493

4.  Serum albumin and prealbumin predict the poor outcome of traumatic brain injury.

Authors:  Du Chen; Long Bao; Shi-qi Lu; Feng Xu
Journal:  PLoS One       Date:  2014-03-26       Impact factor: 3.240

5.  Distribution of Laboratory Parameters in Trauma Population.

Authors:  Prashant Bhandarkar; Ranabir Pal; Ashok Munivenkatappa; Nobhojit Roy; Vineet Kumar; Amit Agrawal
Journal:  J Emerg Trauma Shock       Date:  2018 Jan-Mar

6.  Comparison of admission serum albumin and hemoglobin as predictors of outcome in children with moderate to severe traumatic brain injury: A retrospective study.

Authors:  Hong-Chun Luo; Yue-Qiang Fu; Cheng-Yan You; Cheng-Jun Liu; Feng Xu
Journal:  Medicine (Baltimore)       Date:  2019-11       Impact factor: 1.817

  6 in total

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