Modeling the return to consciousness after severe traumatic brain injury at a large academic level 1 trauma center

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  • 1 Department of Neurological Surgery, Stony Brook University School of Medicine, Stony Brook, New York;
  • 2 Department of Emergency Medicine, Christiana Care Health System, Newark, Delaware; and
  • 3 Department of Rehabilitation Medicine, Icahn School of Medicine at Mount Sinai, New York, New York
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OBJECTIVE

Severe traumatic brain injury (sTBI) carries significant morbidity and mortality. It remains difficult to counsel families on functional prognosis and plan research initiatives aimed at treating traumatic coma. In order to better address these problems, the authors set out to develop statistical models using retrospective data to identify admission characteristics that correlate with time until the return of consciousness, defined as the time to follow commands (TFC). These results were then used to create a TFC score, allowing for rapid identification of patients with predicted prolonged TFC.

METHODS

Data were reviewed and collected from medical records of sTBI patients with Glasgow Coma Scale (GCS) motor subscores ≤ 5 who were admitted to Stony Brook University Hospital from January 2011 to July 2018. Data were used to calculate descriptive statistics and build binary logistic regression models to identify admission characteristics that correlated with in-hospital mortality and in-hospital command-following. A Cox proportional hazards model was used to identify admission characteristics that correlated with the length of TFC. A TFC score was developed using the significant variables identified in the Cox regression model.

RESULTS

There were 402 adult patients who met the inclusion criteria for this study. The average age was 50.5 years, and 122 (30.3%) patients were women. In-hospital mortality was associated with older age, higher Injury Severity Score (ISS), higher Rotterdam score (head CT grading system), and the presence of bilateral fixed and dilated pupils (p < 0.01). In-hospital command-following was anticorrelated with age, ISS, Rotterdam score, and the presence of a single fixed and dilated pupil (p < 0.05). TFC was anticorrelated with age, ISS, Rotterdam score, and the presence of a single fixed and dilated pupil. Additionally, patients who sustained injuries from falls from standing height had a shorter average TFC. The 3 significant variables from the Cox regression model that explained the most variance were used to create a 4-point TFC score. The most significant of these characteristics were Rotterdam head CT scores, high impact traumas, and the presence of a single fixed and dilated pupil. Importantly, the presence of a single fixed and dilated pupil was correlated with longer TFC but no increase in likelihood of in-hospital mortality.

CONCLUSIONS

The creation of the 4-point TFC score will allow clinicians to quickly identify patients with predicted prolonged TFC and estimate the likelihood of command-following at different times after injury. Discussions with family members should take into account the likelihood that patients will return to consciousness and survive after TBI.

ABBREVIATIONS AIS = Abbreviated Injury Scale; AUC = area under the curve; GCS = Glasgow Coma Scale; ISS = Injury Severity Score; LOS = length of stay; sTBI = severe traumatic brain injury; TFC = time to follow commands.

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Contributor Notes

Correspondence Charles B. Mikell: Stony Brook University School of Medicine, Stony Brook, NY. charles.mikell@stonybrookmedicine.edu.

INCLUDE WHEN CITING Published online June 14, 2019; DOI: 10.3171/2019.2.JNS183568.

Disclosures The authors report no conflict of interest concerning the materials or methods used in this study or the findings specified in this paper.

  • 1

    Baker SP, O’Neill B, Haddon W Jr, Long WB: The injury severity score: a method for describing patients with multiple injuries and evaluating emergency care. J Trauma 14:187196, 1974

    • Search Google Scholar
    • Export Citation
  • 2

    Brennan PM, Murray GD, Teasdale GM: Simplifying the use of prognostic information in traumatic brain injury. Part 1: The GCS-Pupils score: an extended index of clinical severity. J Neurosurg 128:16121620, 2018

    • Search Google Scholar
    • Export Citation
  • 3

    Chamoun RB, Robertson CS, Gopinath SP: Outcome in patients with blunt head trauma and a Glasgow Coma Scale score of 3 at presentation. J Neurosurg 111:683687, 2009

    • Search Google Scholar
    • Export Citation
  • 4

    Cox DR: Regression models and life-tables. J R Stat Soc Series B Stat Methodol 34:187220, 1972

  • 5

    Foreman BP, Caesar RR, Parks J, Madden C, Gentilello LM, Shafi S, : Usefulness of the abbreviated injury score and the injury severity score in comparison to the Glasgow Coma Scale in predicting outcome after traumatic brain injury. J Trauma 62:946950, 2007

    • Search Google Scholar
    • Export Citation
  • 6

    Maas AI, Hukkelhoven CW, Marshall LF, Steyerberg EW: Prediction of outcome in traumatic brain injury with computed tomographic characteristics: a comparison between the computed tomographic classification and combinations of computed tomographic predictors. Neurosurgery 57:11731182, 2005

    • Search Google Scholar
    • Export Citation
  • 7

    Roozenbeek B, Chiu YL, Lingsma HF, Gerber LM, Steyerberg EW, Ghajar J, : Predicting 14-day mortality after severe traumatic brain injury: application of the IMPACT models in the brain trauma foundation TBI-trac® New York State database. J Neurotrauma 29:13061312, 2012

    • Search Google Scholar
    • Export Citation
  • 8

    Roozenbeek B, Maas AI, Menon DK: Changing patterns in the epidemiology of traumatic brain injury. Nat Rev Neurol 9:231236, 2013

  • 9

    Sterling P, Laughlin S: Principles of Neural Design. Cambridge, MA: MIT Press, 2015

  • 10

    Steyerberg EW, Mushkudiani N, Perel P, Butcher I, Lu J, McHugh GS, : Predicting outcome after traumatic brain injury: development and international validation of prognostic scores based on admission characteristics. PLoS Med 5:e165, 2008

    • Search Google Scholar
    • Export Citation
  • 11

    Stocchetti N, Carbonara M, Citerio G, Ercole A, Skrifvars MB, Smielewski P, : Severe traumatic brain injury: targeted management in the intensive care unit. Lancet Neurol 16:452464, 2017

    • Search Google Scholar
    • Export Citation
  • 12

    Vedantam A, Robertson CS, Gopinath SP: Clinical characteristics and temporal profile of recovery in patients with favorable outcomes at 6 months after severe traumatic brain injury. J Neurosurg 129:234240, 2018

    • Search Google Scholar
    • Export Citation
  • 13

    Whyte J, Katz D, Long D, DiPasquale MC, Polansky M, Kalmar K, : Predictors of outcome in prolonged posttraumatic disorders of consciousness and assessment of medication effects: a multicenter study. Arch Phys Med Rehabil 86:453462, 2005

    • Search Google Scholar
    • Export Citation

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