Predicting outcome after traumatic brain injury: practical prognostic models based on large cohort of international patients

P Perel, M Arango, T Clayton, P Edwards, E Komolafe, S Pocock, I Roberts, H Shakur, Ewout Steyerberg, S Yutthakasemsunt

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913 Citations (Scopus)

Abstract

Objective To develop and validate practical prognostic models for death at 14 days and for death or severe disability six months after traumatic brain injury. Design Multivariable logistic regression to select variables that were independently associated with two patient outcomes. Two models designed: "basic" model (demographic and clinical variables only) and "CT" model (basic model plus results of computed tomography). The models were subsequently developed for high and low-middle income countries separately. Setting Medical Research Council (MRC) CRASH Trial. Subjects 10 008 patients with traumatic brain injury. Models externally validated in a cohort of 8509. Results The basic model included four predictors: age, Glasgow coma scale, pupil reactivity, and the presence of major extracranial injury. The CT model also included the presence of petechial haemorrhages, obliteration of the third ventricle or basal cisterns, subarachnoid bleeding, midline shift, and non-evacuated haematoma. In the derivation sample the models showed excellent discrimination (C statistic above 0.80). The models showed good calibration graphically. The Hosmer-Lemeshow test also indicated good calibration, except for the CT model in low-middle income countries. External validation for unfavourable outcome at six months in high income countries showed that basic and CT models had good discrimination (C statistic 0.77 for both models) but poorer calibration. Conclusion Simple prognostic models can be used to obtain valid predictions of relevant outcomes in patients with traumatic brain injury.
Original languageUndefined/Unknown
Pages (from-to)425-429
Number of pages5
JournalBritish Medical Journal
Volume336
Issue number7641
Publication statusPublished - 2008

Research programs

  • EMC NIHES-02-65-01

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