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Introduction: Low systolic blood pressure (SBP) is an important secondary insult following traumatic brain injury (TBI), but its exact relationship with outcome is not well characterised. Although a SBP of <90 mmHg represents the threshold for hypotension in consensus TBI treatment guidelines, recent studies suggest redefining hypotension at higher levels. This study therefore aimed to fully characterise the association between admission SBP and mortality to further inform resuscitation endpoints., Methods: We conducted a multicentre cohort study using data from the largest European trauma registry. Consecutive adult patients with AIS head scores >2 admitted directly to specialist neuroscience centres between 2005 and July 2012 were studied. Multilevel logistic regression models were developed to examine the association between admission SBP and 30 day inpatient mortality. Models were adjusted for confounders including age, severity of injury, and to account for differential quality of hospital care., Results: 5057 patients were included in complete case analyses. Admission SBP demonstrated a smooth u-shaped association with outcome in a bivariate analysis, with increasing mortality at both lower and higher values, and no evidence of any threshold effect. Adjusting for confounding slightly attenuated the association between mortality and SBP at levels <120 mmHg, and abolished the relationship for higher SBP values. Case-mix adjusted odds of death were 1.5 times greater at <120 mmHg, doubled at <100 mmHg, tripled at <90 mmHg, and six times greater at SBP<70 mmHg, p<0.01., Conclusions: These findings indicate that TBI studies should model SBP as a continuous variable and may suggest that current TBI treatment guidelines, using a cut-off for hypotension at SBP<90 mmHg, should be reconsidered., (Copyright © 2013 Elsevier Ltd. All rights reserved.)

Background: Head injury is the leading cause of death in trauma. UK national guidelines have recommended that all patients with severe head injury (SHI) should be treated in neuroscience centers. The aim of this study was to investigate the effect of specialist neuroscience care on mortality after SHI., Methods: We conducted a cohort study using prospectively recorded data from the largest European trauma registry, for adult patients presenting with blunt trauma between 2003 and 2009. Mortality and unadjusted odds of death were compared for patients with SHI treated in neuroscience units (NSU) versus nonspecialist centers. To control for confounding, odds of death associated with non-NSU care were calculated using propensity score-adjusted multivariate logistic regression (explanatory covariates: age, Glasgow Coma Score, Injury Severity Score, treatment center). Sensitivity analyses were performed to study possible bias arising from selective enrollment, from loss to follow-up, and from hidden confounders., Results: 5411 patients were identified with SHI between 2003 and 2009, with 1485 (27.4%) receiving treatment entirely in non-NSU centers. SHI management in a non-NSU was associated with a 11% increase in crude mortality (P<0.001) and 1.72-fold (95% confidence interval: 1.52-1.96) increase in odds of death. The case mix adjusted odds of death for patients treated in a non-NSU unit with SHI was 1.85 (95% confidence interval: 1.57-2.19). These results were not significantly changed in sensitivity analyses examining selective enrollment or loss to follow-up, and were robust to potential bias from unmeasured confounders., Conclusions: Our data support current national guidelines and suggest that increasing transfer rates to NSUs represents an important strategy in improving outcomes in patients with SHI.

Unlabelled: Trauma management systems have grown in response to regional variations in trauma population, geographical conditions and the provisions of care. National Trauma Registries are being established to improve patient outcomes. However international comparisons could provide the potential to record regional performance, identify and share examples of best practice. To assess whether it was possible to compare data currently being collected by a number of trauma services across Europe, a group was established to develop a common core dataset and to assess the feasibility of collecting anonymised data., Method: A series of meetings with European collaborators led to the creation of a group entitled EuroTARN. A website was developed in 2002 and interested parties were invited to submit suggestions for a European dataset using an online version of the Delphi technique. A core dataset was created in 2003 and in 2004 participants were invited to submit a summary of past cases online via the EuroTARN Website., Results: Representatives from 14 countries met and corresponded to create the core dataset. During a trial data collection phase 14 institutions from 11 countries submitted unadjusted mortality data for over 21,500 cases with injury severity Scores of over 15 including information on multiply injured and head injured patients. The results demonstrated that there were observed differences in trauma outcome for similar groups of patients., Conclusion: It is possible to collect and collate outcome data from established trauma registries across Europe with minimal additional infrastructure using a web-based system. Initial analysis of the results reveals significant international variations. The network has potential as a source of data for epidemiological and clinical research and for optimal trauma system design across Europe.

Background: In the Trauma Audit and Research Network (TARN), currently the largest trauma network in Europe, outcome prediction is performed using the TRISS methodology since 1989. Its database contains 200,000 hospital admissions from 110 hospitals over the country, but a large amount of data is lost for the modelling because of missing data. To improve some of the shortcomings of TRISS a new model was developed., Methods: The data for modelling consisted of 100,399 hospital trauma admissions over the period 1996 to 2001. Using the Glasgow Coma Score (GCS) instead of RTS has dramatically reduced the number of missing cases. Gender and its interaction with age have also been included in the model. The model was tested on different subsets of cases traditionally excluded, such as children, those with penetrating injuries, and ventilated and transferred patients. The new model included all those subsets using age, a transformation of ISS, GCS, gender and gender by age interaction as predictors., Results: The model has shown a good discriminant ability tested by the area under the receiver operating characteristic (AROC) curve. The values of the AROC for the new model were 0.947 (95% CI: 0.943-0.951) on the prediction set and 0.952 (95% CI: 0.946-0.957) on the validation set compared respectively with 0.937 (95% CI: 0.932-0.943) and 0.941 (95% CI: 0.936-0.952) for TRISS., Conclusion: The new model has enabled us to include most of the cases that were excluded under the TRISS's inclusion criteria, less missing data are incurred and the predictive performance was significantly better than that of the TRISS model as shown by the AROC curves.