BACKGROUND:Several prognostic models to predict outcome in traumatic brain injury (TBI) have been developed, but few are externally validated. We aimed to validate the International Mission on Prognosis and Analysis of Clinical Trials in TBI (IMPACT) prognostic models in a recent unselected patient cohort and to assess the additional prognostic value of extracranial injury. METHODS:The Prospective Observational COhort Neurotrauma (POCON) registry contains 508 patients with moderate or severe TBI, who were admitted in 2008 and 2009 to five trauma centers in the Netherlands. We predicted the probability of mortality and unfavorable outcome at 6 months after injury with the IMPACT prognostic models. We studied discrimination (area under the curve [AUC]) and calibration. We added the extracranial component of the Injury Severity Score (ISS) to the models and calculated the increase in AUC. RESULTS:The IMPACT models had an adequate discrimination in the POCON registry, with AUCs in the external validation between 0.85 and 0.90 for mortality and between 0.82 and 0.87 for unfavorable outcome. Observed outcomes agreed well with predicted outcomes. Adding extracranial injury slightly improved predictions in the overall population (unfavorable outcome: AUC increase of 0.002, p = 0.02; mortality: AUC increase of 0.000, p = 0.37) but more clearly in patients with moderate TBI (unfavorable outcome: AUC increase of 0.008, p G 0.01, mortality: AUC increase of 0.012, p = 0.02) and patients with minor computed tomographic result abnormalities (unfavorable outcome: AUC increase of 0.013, p G 0.01; mortality: AUC increase of 0.001, p = 0.08). CONCLUSION:The IMPACT models performed well in a recent series of TBI patients. We found some additional impact of extracranial injury on outcome, specifically in patients with less severe TBI or minor computed tomographic result abnormalities. (J Trauma Acute Care Surg. 2013;74: 639Y646.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.