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Lookup NU author(s): Professor Sarah O'Brien
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Primary objective: To identify which tool (a model, a biomarker or a combination of these) has better prognostic strength in traumatic brain injury (TBI). Design and methods: Data of 100 patients were analysed. TBI prognostic model B, constructed in Trauma Audit and Research Network (TARN), was run on the dataset and then S100B was added to this model. Another model was developed containing only S100B and, subsequently, other important predictors were added to assess the enhancement of the predictive power. The outcome measures were survival and favourable outcome. Results: No difference between performance of the prognostic model or S100B in isolation is observed. Addition of S100B to the prognostic model improves the performance (e.g. AUC, R2 Nagelkerke and classification accuracy of TARN model B to predict survival increase respectively from 0.66, 0.11 and 70% to 0.77, 0.25 and 75%). Similarly, the predictive power of S100B increases by adding other predictors (e.g. AUC (0.69 vs. 0.79), R2 Nagelkerke (0.15 vs. 0.30) and classification accuracy (73% vs. 77%) for survival prediction). Conclusion: A better prognostic tool than those currently available may be a combination of clinical predictors with a biomarker. © 2014 Informa UK Ltd. All rights reserved: reproduction in whole or part not permitted.
Author(s): Lesko MM, O'Brien SJ, Childs C, Bouamra O, Rainey T, Lecky F
Publication type: Article
Publication status: Published
Journal: Brain Injury
Online publication date: 21/03/2014
Acceptance date: 28/01/2014
ISSN (print): 0269-9052
ISSN (electronic): 1362-301X
Publisher: Informa Healthcare
PubMed id: 24655224
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