Helicopter and ground emergency medical services transportation to hospital after major trauma in England: a comparative cohort study

Background: The utilization of helicopter emergency medical services (HEMS) in modern trauma systems has been a source of debate for many years. This study set to establish the true impact of HEMS in England on survival for patients with major trauma. Methods: A comparative cohort design using prospectively recorded data from the UK Trauma Audit and Research Network registry. 279 107 patients were identified between January 2012 and March 2017. The primary outcome measure was risk adjusted in-hospital mortality within propensity score matched cohorts using logistic regression analysis. Subset analyses were performed for subjects with prehospital Glasgow Coma Scale 29 and systolic blood pressure <90. Results: The analysis was based on 61 733 adult patients directly admitted to major trauma centers: 54 185 ground emergency medical services (GEMS) and 7548 HEMS. HEMS patients were more likely male, younger, more severely injured, more likely to be victims of road traffic collisions and intubated at scene. Crude mortality was higher for HEMS patients. Logistic regression demonstrated a 15% reduction in the risk adjusted odds of death (OR=0.846; 95% CI 0.684 to 1.046) in favor of HEMS. When analyzed for patients previously noted to benefit most from HEMS, the odds of death were reduced further but remained statistically consistent with no effect. Sensitivity analysis on 5685 patients attended by a doctor on scene but transported by GEMS demonstrated a protective effect on mortality versus the standard GEMS response (OR 0.77; 95% CI 0.62 to 0.95). Discussion: This prospective, level 3 cohort analysis demonstrates a non-significant survival advantage for patients transported by HEMS versus GEMS. Despite the large size of the cohort, the intrinsic mismatch in patient demographics limits the ability to statistically assess HEMS true benefit. It does, however, demonstrate an improved survival for patients attended by doctors on scene in addition to the GEMS response. Improvements in prehospital data and increased trauma unit reporting are required to accurately assess HEMS clinical and cost-effectiveness

Cross-validation of two prognostic trauma scores in severely injured patients

Introduction Trauma scoring systems are important tools for outcome prediction and severity adjustment that informs trauma quality assessment and research. Discrimination and precision of such systems is tested in validation studies. The German TraumaRegister DGU® (TR-DGU) and the Trauma Audit and Research Network (TARN) from the UK agreed on a cross-validation study to validate their prediction scores (RISC II and PS14, respectively). Methods Severe trauma patients with an Injury Severity Score (ISS) ≥ 9 documented in 2015 and 2016 were selected in both registries (primary admissions only). The predictive scores from each registry were applied to the selected data sets. Observed and predicted mortality were compared to assess precision; area under the receiver operating characteristic curve was used for discrimination. Hosmer–Lemeshow statistic was calculated for calibration. A subgroup analysis including patients treated in intensive care unit (ICU) was also carried out. Results From TR-DGU, 40,638 patients were included (mortality 11.7%). The RISC II predicted mortality was 11.2%, while PS14 predicted 16.9% mortality. From TARN, 64,622 patients were included (mortality 9.7%). PS14 predicted 10.6% mortality, while RISC II predicted 17.7%. Despite the identical cutoff of ISS ≥ 9, patient groups from both registries showed considerable difference in need for intensive care (88% versus 18%). Subgroup analysis of patients treated on ICU showed nearly identical values for observed and predicted mortality using RISC II. Discussion Each score performed well within its respective registry, but when applied to the other registry a decrease in performance was observed. Part of this loss of performance could be explained by different development data sets: the RISC II is mainly based on patients treated in an ICU, while the PS14 includes cases mainly cared for outside ICU with more moderate injury severity. This is according to the respective inclusion criteria of the two registries. Conclusion External validations of prediction models between registries are needed, but may show that prediction models are not fully transferable to other health-care settings

Age and the distribution of major injury across a national trauma system

Background Trauma places a significant burden on healthcare services, and its management impacts greatly on the injured patient. The demographic of major trauma is changing as the population ages, increasingly unveiling gaps in processes of managing older patients. Key to improving patient care is the ability to characterise current patient distribution. Objectives There is no contemporary evidence available to characterise how age impacts on trauma patient distribution at a national level. Through an analysis of the Trauma Audit Research Network (TARN) database, we describe the nature of Major Trauma in England since the configuration of regional trauma networks, with focus on injury distribution, ultimate treating institution and any transfer in-between. Methods The TARN database was analysed for all patients presenting from April 2012 to the end of October 2017 in NHS England. Results About 307,307 patients were included, of which 63.8% presented directly to a non-specialist hospital (trauma unit (TU)). Fall from standing height in older patients, presenting and largely remaining in TUs, dominates the English trauma caseload. Contrary to perception, major trauma patients currently are being cared for in both specialist (major trauma centres (MTCs)) and non-specialist (TU) hospitals. Paediatric trauma accounts for <5% of trauma cases and is focussed on paediatric MTCs. Conclusions Within adult major trauma patients in England, mechanism of injury is dominated by low level falls, particularly in older people. These patients are predominately cared for in TUs. This work illustrates the reality of current care pathways for major trauma patients in England in the recently configured regional trauma networks

Do patients with diabetes mellitus and polytrauma continue to have worse outcomes?

The management of patients with multiple injuries remains challenging. Patients presenting with comorbidities, such as diabetes mellitus, may have additional unpredictable outcomes with increased mortality. Therefore, we aim to investigate the impact of major trauma centres in the UK on the outcomes of polytrauma patients with diabetes. The Trauma Audit and Research Network was used to identify polytrauma patients presenting to centres in England and Wales between 2012 and 2019. In total, 32,345 patients were thereby included and divided into three groups: 2271 with diabetes, 16,319 with comorbidities other than diabetes and 13,755 who had no comorbidities. Despite an overall increase in diabetic prevalence compared to previously published data, mortality was reduced in all groups, but diabetic patient mortality remained higher than in the other groups. Interestingly, increasing Injury Severity Score (ISS) and age were associated with increasing mortality, whereas the presence of diabetes, even when taking into consideration age, ISS and Glasgow Coma Score, led to an increase in the prediction of mortality with an odds ratio of 1.36 (p < 0.0001). The prevalence of diabetes mellitus in polytrauma patients has increased, and diabetes remains an independent risk factor for mortality following polytrauma

Evaluating the impact of cycle helmet use on severe traumatic brain injury and death in a national cohort of over 11000 pedal cyclists : a retrospective study from the NHS England trauma audit and research network dataset

Objectives In the last 10 years there has been a significant increase in cycle traffic in the UK, with an associated increase in the overall number of cycling injuries. Despite this, and the significant media, political and public health debate into this issue, there remains an absence of studies from the UK assessing the impact of helmet use on rates of serious injury presenting to the National Health Service (NHS) in cyclists. Setting The NHS England Trauma Audit and Research Network (TARN) Database was interrogated to identify all adult (≥16 years) patients presenting to hospital with cycling-related major injuries, during a period from 14 March 2012 to 30 September 2017 (the last date for which a validated dataset was available). Participants 11 patients met inclusion criteria. Data on the use of cycling helmets were available in 6621 patients. Outcome measures TARN injury descriptors were used to compare patterns of injury, care and mortality in helmeted versus non-helmeted cohorts. Results Data on cycle helmet use were available for 6621 of the 11 192 cycle-related injuries entered onto the TARN Database in the 66 months of this study (93 excluded as not pedal cyclists). There was a significantly higher crude 30-day mortality in un-helmeted cyclists 5.6% (4.8%–6.6%) versus helmeted cyclists 1.8% (1.4%–2.2%) (p<0.001). Cycle helmet use was also associated with a reduction in severe traumatic brain injury (TBI) 19.1% (780, 18.0%–20.4%) versus 47.6% (1211, 45.6%–49.5%) (p<0.001), intensive care unit requirement 19.6% (797, 18.4%–20.8%) versus 27.1% (691, 25.4%–28.9%) (p<0.001) and neurosurgical intervention 2.5% (103, 2.1%–3.1%) versus 8.5% (217, 7.5%–9.7%) (p<0.001). There was a statistically significant increase in chest, spinal, upper and lower limb injury in the helmeted group in comparison to the un-helmeted group (all p<0.001), though in a subsequent analysis of these anatomical injury patterns, those cyclists wearing helmets were still found to have lower rates of TBI. In reviewing TARN injury codes for specific TBI and facial injuries, there was a highly significant decrease in rates of impact injury between cyclists wearing helmets and those not. Conclusions This study suggests that there is a significant correlation between use of cycle helmets and reduction in adjusted mortality and morbidity associated with TBI and facial injury

The impact of age on major orthopaedic trauma: an analysis of the United Kingdom Trauma Audit Research Network database.

AIMS: To compare the early management and mortality of older patients sustaining major orthopaedic trauma with that of a younger population with similar injuries. PATIENTS AND METHODS: The Trauma Audit Research Network database was reviewed to identify eligible patients admitted between April 2012 and June 2015. Distribution and severity of injury, interventions, comorbidity, critical care episodes and mortality were recorded. The population was divided into young (64 years or younger) and older (65 years and older) patients. RESULTS: Of 142 765 adults sustaining major trauma, 72 942 (51.09 %) had long bone or pelvic fractures and 45.81% of these were > 65 years old. Road traffic collision was the most common mechanism in the young (40.4%) and, in older people, fall from standing height (80.4%) predominated. The 30 day mortality in older patients with fractures is greater (6.8% versus2.5%), although critical care episodes are more common in the young (18.2%versus9.7%). Older people are less likely to be admitted to critical care beds and are often managed in isolation by surgeons. Orthopaedic surgery is the most common admitting and operating specialty and, in older people, fracture surgery accounted for 82.1% of procedures. CONCLUSION: Orthopaedic trauma in older people is associated with mortality that is significantly greater than for similar fractures in the young. As with the hip fracture population, major trauma in the elderly is a growing concern which highlights the need for a review of admission pathways and shared orthogeriatric care models

Using Abbreviated Injury Scale (AIS) codes to classify Computed Tomography (CT) features in the Marshall System

<p>Abstract</p> <p>Background</p> <p>The purpose of Abbreviated Injury Scale (AIS) is to code various types of Traumatic Brain Injuries (TBI) based on their anatomical location and severity. The Marshall CT Classification is used to identify those subgroups of brain injured patients at higher risk of deterioration or mortality. The purpose of this study is to determine whether and how AIS coding can be translated to the Marshall Classification</p> <p>Methods</p> <p>Initially, a Marshall Class was allocated to each AIS code through cross-tabulation. This was agreed upon through several discussion meetings with experts from both fields (clinicians and AIS coders). Furthermore, in order to make this translation possible, some necessary assumptions with regards to coding and classification of mass lesions and brain swelling were essential which were all approved and made explicit.</p> <p>Results</p> <p>The proposed method involves two stages: firstly to determine all possible Marshall Classes which a given patient can attract based on allocated AIS codes; via cross-tabulation and secondly to assign one Marshall Class to each patient through an algorithm.</p> <p>Conclusion</p> <p>This method can be easily programmed in computer softwares and it would enable future important TBI research programs using trauma registry data.</p

Predicting outcomes after blunt chest wall trauma: development and external validation of a new prognostic model. Crit Care 2014;18:R98

in press). Predicting outcomes after blunt chest wall trauma: development and external validation of a new prognostic model. Critical Care, 18(R98) http://dx.doi.org/doi:10.1186/cc13873 _____________________________________________________________ This article is brought to you by Swansea University. Any person downloading material is agreeing to abide by the terms of the repository licence. Authors are personally responsible for adhering to publisher restrictions or conditions. When uploading content they are required to comply with their publisher agreement and the SHERPA RoMEO database to judge whether or not it is copyright safe to add this version of the paper to this repository. Abstract Introduction: Blunt chest wall trauma accounts for over 15% of all trauma admissions to Emergency Departments worldwide. Reported mortality rates vary between 4 and 60%. Management of this patient group is challenging as a result of the delayed on-set of complications. The aim of this study was to develop and validate a prognostic model that can be used to assist in the management of blunt chest wall trauma. Methods: There were two distinct phases to the overall study; the development and the validation phases. In the first study phase, the prognostic model was developed through the retrospective analysis of all blunt chest wall trauma patients (n = 274) presenting to the Emergency Department of a regional trauma centre in Wales (2009 to 2011). Multivariable logistic regression was used to develop the model and identify the significant predictors for the development of complications. The model&apos;s accuracy and predictive capabilities were assessed. In the second study phase, external validation of the model was completed in a multi-centre prospective study (n = 237) in 2012. The model&apos;s accuracy and predictive capabilities were re-assessed for the validation sample. A risk score was developed for use in the clinical setting. Results: Significant predictors of the development of complications were age, number of rib fractures, chronic lung disease, use of pre-injury anticoagulants and oxygen saturation levels. The final model demonstrated an excellent c-index of 0.96 (95% confidence intervals: 0.93 to 0.98). Conclusions: In our two phase study, we have developed and validated a prognostic model that can be used to assist in the management of blunt chest wall trauma patients. The final risk score provides the clinician with the probability of the development of complications for each individual patient