Predictors of 30-day readmission following hospitalisation with community-acquired pneumonia.

BACKGROUND: There is a paucity of UK data to aid healthcare professionals in predicting which patients hospitalised with community-acquired pneumonia (CAP) are at greatest risk of 30-day readmission and to determine which readmissions may occur soonest. METHODS: An analysis of CAP cases admitted to nine UK hospitals participating in the Advancing Quality Pneumonia Programme. RESULTS: An analysis was performed of 12 157 subjects hospitalised with CAP in the Advancing Quality Programme Database. 26% of those discharged were readmitted within 30 days with readmission predicted by comorbidity including non-metastatic cancer, diabetes with complications and chronic kidney disease. 41% and 66% of readmissions occurred within 7 and 14 days of discharge, respectively. Patients readmitted within 14 days were more likely to have metastatic cancer (6.6% vs 4.5%; p=0.03) compared with those readmitted at 15-30 days. CONCLUSIONS: A quarter of patients hospitalised for CAP are readmitted within 30 days; of those, two-thirds are readmitted within 2 weeks. Further research is required to determine whether such readmissions might be preventable through imple menting measures including in-hospital cross-specialty comorbidity management, convalescence in intermediate care, targeted rehabilitation and advanced care planning.

Epidemiology and aetiology of traumatic cardiac arrest in England and Wales - A retrospective database analysis.

BACKGROUND: Historically, reported survival from traumatic cardiac arrest (TCA) was extremely low. More recent publications have recorded survival to discharge of up to 8%. This improvement is likely to be multi-factorial; however, there are currently no published data describing the epidemiology or aetiology of TCA in England and Wales to guide future practice improvement. METHODS: Population-based analysis of 2009-2015 Trauma Audit and Research Network (TARN) data. The primary aim was to describe the 30-day survival following TCA. Patients of all ages with traumatic cardiac arrest pre-hospital or in the emergency department (ED) were included. Data are described as number (%), and median [interquartile range]. Two-group analysis with Chi-squared test was performed. RESULTS: During the study period 227,944 patients were included in the TARN database. Seven hundred and five (0.3%) suffered TCA: 74.3% were male, aged 44.3 [25.2-83.2] years, ISS 29 [21-75], and 601 (85.2%) had blunt injuries. 612 (86.8%) had a severe traumatic brain injury and or severe haemorrhage. Overall 30-day survival was 7.5% (95%CI 5.6-9.5) - 'pre-hospital only' TCA 11.5%, 'ED only' TCA 3.9%, p<0.02. No patients who were in TCA both pre-hospital and in the ED survived. CONCLUSION: This study has shown that short-term survival from TCA in this large civilian registry is 7.5%. Early and aggressive management of patients with TCA, using protocols that target the reversible causes of TCA, should be initiated. Further work to establish novel ways to manage patients with reversible causes of TCA is indicated. Resuscitation in this patient group is not futile.

Prediction modelling for trauma using comorbidity and 'true' 30-day outcome.

BACKGROUND: Prediction 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. METHODS: Prospectively 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. RESULTS: The 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. CONCLUSIONS: The 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.

The effect of preinjury warfarin use on mortality rates in trauma patients: a European multicentre study.

OBJECTIVE: To define the relationship between preinjury warfarin use and mortality in a large European sample of trauma patients. METHODS: A multicentred study was conducted using data collated from European (predominately English and Welsh) trauma receiving hospitals. Patient data from the Trauma Audit and Research Network database from 2009 to 2013 were analysed. Univariate and multivariate logistic regression was used to estimate OR for mortality associated with preinjury warfarin use in the whole adult trauma cohort and a matched sample of patients comparable in terms of age, gender, GCS, pre-existing medical conditions and injury severity. RESULTS: A total of 136 617 adult trauma patients (2009-2013) were included, with 499 patients reported to be using warfarin therapy at the time of trauma. Preinjury warfarin use was associated with a significantly higher mortality rate at 30 days postinjury compared with the non-users. Following adjustment of age, injury severity and GCS, preinjury warfarin use was associated with increased mortality in trauma patients (adjusted OR 2.14; 95% CI 1.66 to 2.76; p<0.001). In the matched subset, 22% of warfarinised trauma patients died compared with 16.3% of non-warfarinised trauma patients with comparable age, injury severity and GCS (adjusted OR 1.94; 95% CI 1.25 to 3.01; p=0.003). CONCLUSIONS: Preinjury warfarin use has been demonstrated to be an independent predictor of mortality in trauma patients. Clinicians managing major trauma patients on warfarin need to be aware of the vulnerability of this group.

Outcomes of polytrauma patients with diabetes mellitus.

BACKGROUND: The impact of diabetes mellitus in patients with multiple system injuries remains obscure. This study was designed to increase knowledge of outcomes of polytrauma in patients who have diabetes mellitus. METHODS: Data from the Trauma Audit and Research Network was used to identify patients who had suffered polytrauma during 2003 to 2011. These patients were filtered to those with known outcomes, then separated into those with diabetes, those known to have other co-morbidities but not diabetes and those known not to have any co-morbidities or diabetes. The data were analyzed to establish if patients with diabetes had differing outcomes associated with their diabetes versus the other groups. RESULTS: In total, 222 patients had diabetes, 2,558 had no past medical co-morbidities (PMC), 2,709 had PMC but no diabetes. The diabetic group of patients was found to be older than the other groups (P <0.05). A higher mortality rate was found in the diabetic group compared to the non-PMC group (32.4% versus 12.9%), P <0.05). Rates of many complications including renal failure, myocardial infarction, acute respiratory distress syndrome, pulmonary embolism and deep vein thrombosis were all found to be higher in the diabetic group. CONCLUSIONS: Close monitoring of diabetic patients may result in improved outcomes. Tighter glycemic control and earlier intervention for complications may reduce mortality and morbidity.

Models of mortality probability in severe traumatic brain injury: results of the modelling by the UK trauma registry.

Currently available prognostic models in Traumatic Brain Injury (TBI) are derived from historical data sets or from heterogeneous data sets, depending upon the trauma care delivered. The objective of our study was to develop models to predict survival in a recent cohort of TBI patients within a relatively homogeneous trauma care system. Records of patients with brain injury were extracted from the Trauma Audit and Research Network (TARN) database. The relationship of the variables (i.e., age, Glasgow Coma Score [GCS], pupillary reactivity, Injury Severity Score [ISS], Computed Tomography [CT] classifications, classification of various intracranial pathologies, systolic and mean blood pressure, oxygen saturation, and the presence of extracranial injury) to survival at discharge were determined. Stepwise logistical regression analysis was performed to determine the best prognostic model. Two models were derived from data of 802 patients (models A and B). Age, GCS, pupillary reactivity, hypoxia, and brainstem injury are significant predictors in both. However, model A contains ISS in contrast to model B, which contains the presence of brain swelling and major extracranial injury instead. Both models have good predictive performance (model A: area under the Receiver Operating Characteristic [ROC] curve [AUC]=0.92 [95% CI, 0.90-0.95], Nagelkerke R(2), 0.62; model B: AUC=0.93 [95% CI: 0.91-0.95], Nagelkerke R(2): 0.63). Hence, two accurate and reliable prognostic models were developed from a recent cohort of the TBI population.

Increased mortality associated with cerebral contusions following trauma in the elderly: bad patients or bad management?

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.

Comparing model performance for survival prediction using total Glasgow Coma Scale and its components in traumatic brain injury.

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.

Burns represent a significant proportion of the total serious trauma workload in England and Wales.

Traumatic injury is the leading cause of death in the first four decades of life. However, current estimates for traumatic injury rates fail to take into account burns. The aim of this work was to estimate the contribution of burns to serious traumatic injury in England and Wales. We have determined population-based burns rates using the International Burn Injury Database (iBID, www.ibidb.org) which collects data from regional burn centres, and non-burns rate using data from the Trauma Audit and Research Network (TARN) which collects data from emergency departments (ED, www.TARN.ac.uk). Due to incomplete national coverage of TARN, non-burns rates were estimated using data from 94 EDs that contributed data to TARN. Both non-burn and burns rates were calculated nationally and for each regional burn service catchment area (n=17). Only serious injuries (≥72 h admission or death) were included. Burns rate was 4.7 and non-burns rate 82.7 per 100,000 per year nationally. Burns therefore contributed 5.4% of all serious traumatic injuries. Contribution of burns in different regional burn service catchment areas was between 1.5% and 12%. This data suggests that burns contribute significantly to the overall trauma workload, and should be carefully considered in healthcare planning and policy.

Recent massive blood transfusion practice in England and Wales: view from a trauma registry.

BACKGROUND: Few studies have characterised massive blood transfusion (MBT) practice in UK trauma. This study describes the Trauma Audit and Research Network experience of MBT over a 4-year period, and examines variables predictive of MBT and mortality following MBT. METHODS: Prospectively collected data between 2005 and 2009 from the Trauma Audit and Research Network database were analysed. MBT incidence was examined, and patient characteristics, blood component usage and mortality compared to non-MBT patients. Clinical and injury features predictive of massive transfusion, and risk factors predictive of death in MBT, were analysed using multivariate logistic regression. RESULTS: 157 patients (0.4%) received MBT, with a mortality rate of 40.3%. MBT patients were younger, more likely to be male and to have sustained more severe trauma (median age 39.2 years, median Injury Severity Score 27, 78% male, p<0.01). No patients received platelets and fresh frozen plasma (FFP) in 1:1 ratios with packed red cells. Multivariate analysis showed: age, admission pulse rate, systolic blood pressure, and injury type; thoracic, abdominal, pelvis, were significant predictors of MBT. Injury Severity Score and admission pulse rate were also independent predictors of death in MBT, but level of platelet and FFP use were not found to be statistically significant. CONCLUSION: 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.

The effect of specialist neurosciences care on outcome in adult severe head injury: a cohort study.

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.

The effect of an organized trauma system on mortality in major trauma involving serious head injury: a comparison of the United kingdom and victoria, australia.

OBJECTIVE: To compare outcomes following major trauma involving serious head injury managed in an inclusive trauma system (Victoria, Australia) and a setting where rationalization of trauma services is absent (England/Wales). BACKGROUND: The introduction of regionalized trauma systems has the potential to reduce preventable deaths, but their uptake has been slow around the world. Improved understanding of the benefits and limitations of different systems of trauma care requires comparison across systems. METHODS: Mortality outcomes following major trauma involving serious head injury managed in the 2 settings were compared using multivariate logistic regression. Data pertaining to the period July 2001 to June 2006 (inclusive) were extracted from the Trauma Audit and Research Network (TARN) in the United Kingdom and the Victorian State Trauma Registry (VSTR) in Australia. RESULTS: A total of 4064 (VSTR) and 6024 (TARN) cases were provided for analysis. The odds of death for TARN cases were significantly higher than those for VSTR cases [odds ratio = 2.15, 95% confidence interval = 1.95-2.37]. After adjusting for age, gender, cause of injury, head injury severity, Glasgow Coma Scale score, and Injury Severity Score, TARN cases remained at elevated odds of death (3.22; 95% confidence interval = 2.84-3.65) compared with VSTR cases. CONCLUSIONS: 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.

Applying composite performance measures to trauma care.

BACKGROUND: To investigate the association between a number of hospital level composite index methodologies developed from trauma indicators with inhospital mortality. METHODS: Data from January 2001 to December 2006 were extracted from the Victorian State Trauma Registry (Australia) and the Trauma Audit and Research Network (United Kingdom). Three composite methods were explored, including two denominator-based weight approaches and a factor analysis technique. The association between the composite measures and the count of inhospital mortality was investigated using Poisson regression models adjusting for expected deaths per hospital using the Trauma Injury Severity Score methodology. RESULTS: Composite scores were calculated per hospital, per year. The composite score was entered in statistical models as a raw score, and the mortality difference across the central 50% of the composite index was ascertained. In total, 9,218 patients were included and were distributed across 14 hospitals. Composite scores demonstrated an inverse relationship with risk-adjusted inhospital mortality. From the 25th to the 75th percentile of each composite, mortality decreased by 11.99%, 13.58%, and 16.13% (p < 0.05). CONCLUSION: Trauma composite indices demonstrate construct validity when used as measures of hospital level process and represent potentially useful methods of analyzing and reporting quality indicators.