Early prediction of outcome after severe traumatic brain injury: A simple and practical model

Sandro Rizoli, Ashley Petersen, Eileen Bulger, Raul Coimbra, Jeffrey D. Kerby, Joseph Minei, Laurie Morrison, Avery Nathens, Martin Schreiber, Airton Leonardo de Oliveira Manoel

Research output: Contribution to journalArticle

6 Citations (Scopus)

Abstract

Background: Traumatic brain injury (TBI) is a heterogeneous syndrome with a broad range of outcome. We developed a simple model for long-term outcome prognostication after severe TBI. Methods: Secondary data analysis of a large multicenter randomized trial. Patients were grouped according to 6-month extended Glasgow outcome scale (eGOS): poor-outcome (eGOS ≤ 4; severe disability or death) and acceptable outcome (eGOS > 4; no or moderate disability). A prediction decision tree was built using binary recursive partitioning to predict poor or acceptable 6-month outcome. Comparison to two previously published and validated models was made. Results: The decision tree included the predictors of head Abbreviated Injury Scale (AIS) severity, the Marshall computed tomography score, and pupillary reactivity. All patients with a head AIS severity of 5 were predicted to have a poor outcome. In patients with head AIS severity < 5, the model predicted an acceptable outcome for (1) those with Marshall score of 1, and (2) those with Marshall score above 1 but with reactive pupils at admission. The decision tree had a sensitivity of 72.3 % (95 % CI: 66.4-77.6 %) and specificity of 62.5 % (95 % CI: 54.9-69.6 %). The proportion correctly classified for the comparison models was similar to our model. Our model was more apt at correctly classifying those with poor outcome but more likely to misclassify those with acceptable outcome than the comparison models. Conclusion: Predicting long-term outcome early after TBI remains challenging and inexact. This model could be useful for research and quality improvement studies to provide an early assessment of injury severity, but is not sufficiently accurate to guide decision-making in the clinical setting.

Original languageEnglish (US)
Article number32
JournalBMC Emergency Medicine
Volume16
Issue number1
DOIs
StatePublished - Aug 24 2016

Fingerprint

Abbreviated Injury Scale
Glasgow Outcome Scale
Decision Trees
Craniocerebral Trauma
Pupil
Quality Improvement
Multicenter Studies
Tomography
Wounds and Injuries
Research
carbosulfan
Traumatic Brain Injury

Keywords

  • Outcome measures
  • Prognostic models
  • Recovery
  • Traumatic brain injury

ASJC Scopus subject areas

  • Emergency Medicine

Cite this

Rizoli, S., Petersen, A., Bulger, E., Coimbra, R., Kerby, J. D., Minei, J., ... de Oliveira Manoel, A. L. (2016). Early prediction of outcome after severe traumatic brain injury: A simple and practical model. BMC Emergency Medicine, 16(1), [32]. https://doi.org/10.1186/s12873-016-0098-x

Early prediction of outcome after severe traumatic brain injury : A simple and practical model. / Rizoli, Sandro; Petersen, Ashley; Bulger, Eileen; Coimbra, Raul; Kerby, Jeffrey D.; Minei, Joseph; Morrison, Laurie; Nathens, Avery; Schreiber, Martin; de Oliveira Manoel, Airton Leonardo.

In: BMC Emergency Medicine, Vol. 16, No. 1, 32, 24.08.2016.

Research output: Contribution to journalArticle

Rizoli, S, Petersen, A, Bulger, E, Coimbra, R, Kerby, JD, Minei, J, Morrison, L, Nathens, A, Schreiber, M & de Oliveira Manoel, AL 2016, 'Early prediction of outcome after severe traumatic brain injury: A simple and practical model', BMC Emergency Medicine, vol. 16, no. 1, 32. https://doi.org/10.1186/s12873-016-0098-x
Rizoli, Sandro ; Petersen, Ashley ; Bulger, Eileen ; Coimbra, Raul ; Kerby, Jeffrey D. ; Minei, Joseph ; Morrison, Laurie ; Nathens, Avery ; Schreiber, Martin ; de Oliveira Manoel, Airton Leonardo. / Early prediction of outcome after severe traumatic brain injury : A simple and practical model. In: BMC Emergency Medicine. 2016 ; Vol. 16, No. 1.
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