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

J Neurotrauma. 2012 Nov 20;29(17):2613-24. doi: 10.1089/neu.2012.2468. Epub 2012 Nov 14.

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.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Adult
  • Age Factors
  • Aged
  • Aged, 80 and over
  • Biomarkers / blood
  • Blood Chemical Analysis
  • Brain Injuries / blood*
  • Brain Injuries / pathology
  • Brain Injuries / psychology
  • Female
  • Glasgow Coma Scale
  • Glasgow Outcome Scale
  • Hematologic Tests
  • Humans
  • Linear Models
  • Logistic Models
  • Male
  • Middle Aged
  • Multivariate Analysis
  • Nonlinear Dynamics
  • Predictive Value of Tests
  • Prognosis
  • Sex Factors
  • Treatment Outcome
  • Young Adult

Substances

  • Biomarkers