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

ABSTRACT: 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.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.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?

SUBMITTER: Rizoli S 

PROVIDER: S-EPMC4995825 | biostudies-literature | 2016 Aug

REPOSITORIES: biostudies-literature

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

Rizoli Sandro S   Petersen Ashley A   Bulger Eileen E   Coimbra Raul R   Kerby Jeffrey D JD   Minei Joseph J   Morrison Laurie L   Nathens Avery A   Schreiber Martin M   de Oliveira Manoel Airton Leonardo AL  

BMC emergency medicine 20160824 1

<h4>Background</h4>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.<h4>Methods</h4>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 bu  ...[more]

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