Prognostic Value of Hemorrhagic Brainstem Injury on Early Computed Tomography: A TRACK-TBI Study

Abstract

Background

Traumatic brainstem injury has yet to be incorporated into widely used imaging classification systems for traumatic brain injury (TBI), and questions remain regarding prognostic implications for this TBI subgroup. To address this, retrospective data on patients from the multicenter prospective Transforming Research and Clinical Knowledge in TBI study were studied.

Methods

Patients with brainstem and cerebrum injury (BSI+) were matched by age, sex, and admission Glasgow Coma Scale (GCS) score to patients with cerebrum injuries only. All patients had an interpretable head computed tomography (CT) scan from the first 48 hours after injury and a 6-month Glasgow Outcome Scale Extended (GOSE) score. CT scans were reviewed for brainstem lesions and, when present, characterized by location, size, and type (traumatic axonal injury, contusion, or Duret hemorrhage). Clinical, demographic, and outcome data were then compared between the two groups.

Results

Mann–Whitney U-tests showed no significant difference in 6-month GOSE scores in patients with BSI+ (mean 2.7) compared with patients with similar but only cerebrum injuries (mean 3.9), although there is a trend (p = 0.10). However, subclassification by brainstem lesion type, traumatic axonal injury (mean 4.0) versus Duret hemorrhage or contusion (mean 1.4), did identify a proportion of BSI+ with significantly less favorable outcome (p = 0.002). The incorporation of brainstem lesion type (traumatic axonal injury vs. contusion/Duret), along with GCS into a multivariate logistic regression model of favorable outcome (GOSE score 4–8) did show a significant contribution to the prognostication of this brainstem injury subgroup (odds ratio 0.08, 95% confidence interval 0.00–0.67, p = 0.01).

Conclusions

These findings suggest two groups of patients with brainstem injuries may exist with divergent recovery potential after TBI. These data support the notion that newer CT imaging classification systems may augment traditional clinical measures, such as GCS in identifying those patients with TBI and brainstem injuries that stand a higher chance of favorable outcome.

Appendix: TRACK-TBI Investigators

Opeolu Adeoye, MD, University of Cincinnati; Neeraj Badjatia, MD, University of Maryland; Kim Boase, University of Washington; Yelena Bodien, PhD, Massachusetts General Hospital; M. Ross Bullock, MD PhD, University of Miami; Randall Chesnut, MD, University of Washington; John D. Corrigan, PhD, ABPP, Ohio State University; Karen Crawford, University of Southern California; Ramon Diaz-Arrastia, MD PhD, University of Pennsylvania; Sureyya Dikmen, PhD, University of Washington; Ann-Christine Duhaime, MD, MassGeneral Hospital for Children; Richard Ellenbogen, MD, University of Washington; V Ramana Feeser, MD, Virginia Commonwealth University; Adam R. Ferguson, PhD, University of California, San Francisco; Brandon Foreman, MD, University of Cincinnati; Raquel Gardner, University of California, San Francisco; Etienne Gaudette, PhD, University of Southern California; Dana Goldman, PhD, University of Southern California; Luis Gonzalez, TIRR Memorial Hermann; Shankar Gopinath, MD, Baylor College of Medicine; Rao Gullapalli, PhD, University of Maryland; J Claude Hemphill, MD, University of California, San Francisco; Gillian Hotz, PhD, University of Miami; Sonia Jain, PhD, University of California, San Diego; C. Dirk Keene, MD PhD, University of Washington; Frederick K. Korley, MD, PhD, University of Michigan; Joel Kramer, PsyD, University of California, San Francisco; Natalie Kreitzer, MD, University of Cincinnati; Harvey Levin, MD, Baylor College of Medicine; Chris Lindsell, PhD, Vanderbilt University; Joan Machamer, MA, University of Washington; Christopher Madden, MD, UT Southwestern; Alastair Martin, PhD, University of California, San Francisco; Thomas McAllister, MD, Indiana University; Michael McCrea, PhD, Medical College of Wisconsin; Randall Merchant, PhD, Virginia Commonwealth University; Lindsay Nelson, PhD, Medical College of Wisconsin; Laura B. Ngwenya, MD, PhD, University of Cincinnati; Florence Noel, PhD, Baylor College of Medicine; Amber Nolan, MD PhD, University of California, San Francisco; Eva Palacios, PhD, University of California, San Francisco; Daniel Perl, MD, Uniformed Services University; Ava Puccio, PhD, University of Pittsburgh; Miri Rabinowitz, PhD, University of Pittsburgh; Claudia Robertson, MD, Baylor College of Medicine; Jonathan Rosand, MD, MSc, Massachusetts General Hospital; Angelle Sander, PhD, Baylor College of Medicine; Gabriella Satris, University of California, San Francisco; David Schnyer, PhD, UT Austin; Seth Seabury, PhD, University of Southern California; Murray Stein, MD MPH, University of California, San Diego; Sabrina Taylor, PhD, University of California, San Francisco; Arthur Toga, PhD, University of Southern California; Alex Valadka, MD, Virginia Commonwealth University; Mary Vassar, RN MS, University of California, San Francisco; Paul Vespa, MD, University of California, Los Angeles; Kevin Wang, PhD, University of Florida; John K. Yue, MD, University of California, San Francisco; Ross Zafonte, Harvard Medical School.