No abstract

Management of the severely injured patient with an associated head injury in England and Wales, where an organized trauma system is absent, was associated with increased risk-adjusted mortality compared with management of these patients in the inclusive trauma system of Victoria, Australia. This study provides further evidence to support efforts to implement such systems.

The time to death after severe trauma does not follow a trimodal distribution but shows a constantly decreasing incidence.

BackgroundPrediction models for trauma outcome routinely control for age but there is uncertainty about the need to control for comorbidity and whether the two interact. This paper describes recent revisions to the Trauma Audit and Research Network (TARN) risk adjustment model designed to take account of age and comorbidities. In addition linkage between TARN and the Office of National Statistics (ONS) database allows patient's outcome to be accurately identified up to 30 days after injury. Outcome at discharge within 30 days was previously used.MethodsProspectively collected data between 2010 and 2013 from the TARN database were analysed. The data for modelling consisted of 129 786 hospital trauma admissions. Three models were compared using the area under the receiver operating curve (AuROC) for assessing the ability of the models to predict outcome, the Akaike information criteria to measure the quality between models and test for goodness-of-fit and calibration. Model 1 is the current TARN model, Model 2 is Model 1 augmented by a modified Charlson comorbidity index and Model 3 is Model 2 with ONS data on 30 day outcome.ResultsThe values of the AuROC curve for Model 1 were 0.896 (95% CI 0.893 to 0.899), for Model 2 were 0.904 (0.900 to 0.907) and for Model 3 0.897 (0.896 to 0.902). No significant interaction was found between age and comorbidity in Model 2 or in Model 3.ConclusionsThe new model includes comorbidity and this has improved outcome prediction. There was no interaction between age and comorbidity, suggesting that both independently increase vulnerability to mortality after injury.

Age has been identified as an independent risk factor for poor outcome following head injury in the elderly, and postulated reasons for this include nature, nurture, and variations in management. Do elderly head injuries do worse because of a self-fulfilling prophecy of poorer management? The aim of this study was to review the management of patients with cerebral contusions according to age to identify any trends. We retrospectively reviewed prospectively collected national data on cerebral contusion admissions between March 14, 1988, and May 4, 2012, to UK hospitals held in the Trauma Audit and Research Network database. Patients were included in the study if they had cerebral contusion(s) with an abbreviated injury score (AIS) of 3 or more; no other head injury with a AIS score of 4 or more, or no injury in any other body region with AIS score of 3 or more, and known outcome data. In total, 4387 patients met the inclusion criteria. Mortality was found to increase with increasing age (p<0.001). However, time from admission to CT head imaging (p=0.003) and the likelihood of not being transferred to a center with acute neurosurgical care facilities (p<0.001) increased with increasing age, too. Further, there was a significant trend for the most senior grade of doctor to review more younger patients and for only the most junior grade of doctor to review more older patients (both, p<0.001). To conclude, our data suggest differences in management practice may contribute to the observed differences in mortality between younger and older patients suffering brain contusions.

The Glasgow Coma Scale (GCS) score is used in clinical practice for patient assessment and communication among clinicians and also in outcome prediction models such as the Trauma and Injury Severity Score (TRIS). The objective of this study is to determine which GCS subscore is best associated with outcome, taking time of assessment into account. Records of patients with brain injury who presented after 1989 were extracted from the Trauma Audit and Research Network (TARN) database. Using logistic regression, a baseline model was derived with age, Injury Severity Score (ISS), and year of injury as covariates and survival at discharge as the dependent variable. Total GCS, its subscores, and their combinations at various time points were separately added to the baseline model to compare their effect on model performance. The dataset contained 21,657 cases. The total GCS score at scene and its subscores had significantly lower predictive power compared with those recorded on arrival at the Emergency Department (ED) (scene total GCS: Area Under the Curve-AUC: 0.89; 95% confidence interval [CI]: 0.89-0.90) and Nagelkerke R(2) of 0.55, admission total GCS: AUC of 0.91; 95% CI: 0.91-0.91, and Nagelkerke R(2) of 0.59). Eye and verbal subscores had significantly lower performances compared with total GCS, motor subscore, and various combinations of subscores. Motor subscore and total GCS appeared to have similar predictive performance (admission total and motor GCS both had AUC of 0.91 (95% CI: 0.91-0.92) and Nagelkerke R(2) of 0.59 and 0.58, respectively). Motor subscore contains most of the predictive power of the total score. GCS on arrival is a significantly better predictor of outcome than that recorded at scene.

The reduction in odds of death following HI since 2003 is consistent with improved management following the introduction of national HI guidelines and increased treatment of SHI in NSUs.

MBT is a rare event with high mortality in UK trauma. Haemostatic resuscitation is not currently practiced in the UK and the authors were unable to show that FFP and platelet use were significant predictors of survival in MBT.