Introduction: Traumatic Brain Injury (TBI) is a public health problem. It is a pathology that causes significant mortality and disability. Different models have been developed in order to predict the neurological outcomes. Marshall computed tomographic (CT) classification is widely used as a predictor of outcome. However, this grading system lacks useful variables to predict the outcome of the patient, which are subarachnoid/intraventricular hemorrhage, extradural haematoma, and extent of basal cistern compression. We aimed to develop and validate a practical prognostic model that include all the variables above and predict death at six months after TBI.

Methods: Prospectively collected individual patient data were analyzed. The CT model included midline shift over 5 mm, normal, compressed or absent basal cisterns, subarachnoid bleeding, basal bleeding, intraventricular bleeding, contusion and epidural, subdural or intracerebral haematoma. We considered predictors available at admission in logistic regression models to predict mortality at 6 months after TBI. The performance and accuracy of several model was assessment using the Spearman's rank correlation coefficient and the area under the receiver operating characteristic curve (AUC).

Results: A total of 145 patients were recruited for study, median age 33 (15-85) years, and 86.89% were male. The overall mortality was 24.82%. The median GCS of patients was 6 (3-12). The Marshall CT classification discrimination was AUC= 0.646, Helsinki CT Score discrimination was AUC= 0.724, Rotterdam grading discrimination was AUC= 0.735, all these with a low correlation with the outcome (Spearman's rho <0.40). Our model showed the best performance and correlation with 6-month mortality: AUC= 0.7755, Spearman's rho 0,4201, p= 0.000.

Conclusions: Our prognostic mortality CT model showed a great performance and accuracy and can be used to obtain valid predictions of relevant outcomes in patients with TBI.

Patient Care: To clasificate the early porgnosis and mortality in sever TBI patients

Learning Objectives: By the conclusion of this session, participants should be able to: Learn to aplicated a prognostic mortality CT model in patients with TBI

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