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Predicting outcome in severe traumatic brain injury using a simple prognostic model

Simpiwe Sobuwa, Henry Benjamin Hartzenberg, Heike Geduld, Corrie Uys

Abstract


Background. Several studies have made it possible to predict outcome in severe traumatic brain injury (TBI) making it beneficial as an aid for clinical decision-making in the emergency setting. However, reliable predictive models are lacking for resource-limited prehospital settings such as those in developing countries like South Africa.

Objective. To develop a simple predictive model for severe TBI using clinical variables in a South African prehospital setting.

Methods. All consecutive patients admitted at two level-one centres in Cape Town, South Africa, for severe TBI were included. A binary logistic regression model was used, which included three predictor variables: oxygen saturation (SpO2), Glasgow Coma Scale (GCS) and pupil reactivity. The Glasgow Outcome Scale was used to assess outcome on hospital discharge.

Results. A total of 74.4% of the outcomes were correctly predicted by the logistic regression model. The model demonstrated SpO2 (p=0.019), GCS (p=0.001) and pupil reactivity (p=0.002) as independently significant predictors of outcome in severe TBI. Odds ratios of a good outcome were 3.148 (SpO2 ≥90%), 5.108 (GCS 6 - 8) and 4.405 (pupils bilaterally reactive).

Conclusion. This model is potentially useful for effective predictions of outcome in severe TBI. 


Authors' affiliations

Simpiwe Sobuwa, Department of Emergency Medical Sciences, Faculty of Health and Wellness Sciences, Cape Peninsula University of Technology, Cape Town, South Africa

Henry Benjamin Hartzenberg, Division of Neurosurgery, Stellenbosch University, Parow, South Africa

Heike Geduld, Division of Emergency Medicine, University of Cape Town, South Africa

Corrie Uys, Centre for Postgraduate Studies, Cape Peninsula University of Technology, Cape Town, South Africa

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Keywords

Traumatic brain injury; Prehospital; Prognosis

Cite this article

South African Medical Journal 2014;104(7):492-494. DOI:10.7196/SAMJ.7720

Article History

Date submitted: 2013-11-11
Date published: 2014-06-17

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