Abstract PR147

Abstract

Background & Objectives: Predicting long-term neurological outcomes after severe traumatic brain (TBI) is important, but which prognostic model has the best performance remains uncertain. Materials & Methods: This retrospective cohort study included all patients who had severe TBI requiring decompressive craniectomy, between 2004 and 2014, in two neurosurgical centres in Western Australia. Severe disability requiring help with daily living, vegetative state, or death were defined as unfavourable neurological outcomes. Area under the receiver-operating-characteristic curve (AUROC) and slope and intercept of the calibration curve were used to assess discrimination and calibration.of the CRASH (Corticosteroid-Randomisation-After-Significant-Head injury) and IMPACT (International-Mission-For-Prognosis-And-Clinical-Trial) models, respectively. Results: Of the 319 patients included in the study, 118 (37%) had unfavourable neurological outcomes at 18-month after decompressive craniectomy for severe TBI. Both CRASH (AUROC 0.86, 95% confidence interval 0.81–0.90) and IMPACT (AUROC 0.85, 95%CI 0.80–0.89) models were similarly good in discriminating between favourable and unfavourable neurological outcome at 18-month after surgery (p=0.690 for the difference in AUROC derived from the two models). Although both models tended to over-predict the risks of long-term unfavourable outcome, the IMPACT model had a slightly better calibration than the CRASH model (intercept of the calibration curve = -4.1 vs. -5.7, respectively), especially when the predicted risks of unfavourable outcome were <80%. Conclusion: Both CRASH and IMPACT prognostic models were good in discriminating between favourable and unfavourable long-term neurological outcome for patients with severe TBI requiring decompressive craniectomy, but the calibration of the IMPACT full-model was better than the CRASH model. These results suggest that both prognostic models can be used for risk adjustments in randomised controlled trials but the better calibration of the IMPACT model makes it as the preferred model for risk adjustment in observational studies and in providing objective prognostic outcome prediction. Disclosure of Interest: None declared