Project description:BackgroundUp to 40% of combat casualties with a truncal injury die of massive hemorrhage before reaching a surgeon. This hemorrhage can be prevented with damage control resuscitation (DCR) methods, which are focused on replacing shed whole blood by empirically transfusing blood components in a 1:1:1:1 ratio of platelets:fresh frozen plasma:erythrocytes:cryoprecipitate (PLT:FFP:RBC:CRYO). Measurement of hemostatic function with rotational thromboelastometry (ROTEM) may allow optimization of the type and quantity of blood products transfused. Our hypothesis was that incorporating ROTEM measurements into DCR methods at the US Role 3 hospital at Bagram Airfield, Afghanistan would change the standard transfusion ratios of 1:1:1:1 to a product mix tailored specifically for the combat causality.MethodsThis retrospective study collected data from the Department of Defense Trauma Registry to compare transfusion practices and outcomes before and after ROTEM deployment to Bagram Airfield. Over the course of six months, 134 trauma patients received a transfusion (pre-ROTEM) and 85 received a transfusion and underwent ROTEM testing (post-ROTEM). Trauma teams received instruction on ROTEM use and interpretation, with no provision of a specific transfusion protocol, to supplement their clinical judgment and practice.ResultsThe pre and post groups were not significantly different in terms of mortality, massive transfusion protocol activation, mean injury severity score, or coagulation measurements. Despite the difference in size, each group received an equal total number of transfusions. However, the post-ROTEM group received a significant increase in PLT and CRYO transfusions ratios, 4× and 2×, respectively.ConclusionThe introduction of ROTEM significantly improved adherence to DCR practices. The transfusion differences suggest that aggressive DCR without thromboelastometry data may result in reduced hemostatic support and underestimate the need for PLT and CRYO. Thus, future controlled trials should include ROTEM-guided coagulation management in trauma resuscitation.Level of evidenceTherapeutic, level IV.

Project description:BackgroundTo prevent symptomatic heterotopic ossification (HO) and guide primary prophylaxis in patients with combat wounds, physicians require risk stratification methods that can be used early in the postinjury period. There are no validated models to help guide clinicians in the treatment for this common and potentially disabling condition.Questions/purposesWe developed three prognostic models designed to estimate the likelihood of wound-specific HO formation and compared them using receiver operating characteristic (ROC) curve analysis and decision curve analysis (DCA) to determine (1) which model is most accurate; and (2) which technique is best suited for clinical use.MethodsWe obtained muscle biopsies from 87 combat wounds during the first débridement in the United States, all of which were evaluated radiographically for development of HO at a minimum of 2 months postinjury. The criterion for determining the presence of HO was the ability to see radiographic evidence of ectopic bone formation within the zone of injury. We then quantified relative gene expression from 190 wound healing, osteogenic, and vascular genes. Using these data, we developed an Artificial Neural Network, Random Forest, and a Least Absolute Shrinkage and Selection Operator (LASSO) Logistic Regression model designed to estimate the likelihood of eventual wound-specific HO formation. HO was defined as any HO visible on the plain film within the zone of injury. We compared the models accuracy using area under the ROC curve (area under the curve [AUC]) as well as DCA to determine which model, if any, was better suited for clinical use. In general, the AUC compares models based solely on accuracy, whereas DCA compares their clinical utility after weighing the consequences of under- or overtreatment of a particular disorder.ResultsBoth the Artificial Neural Network and the LASSO logistic regression models were relatively accurate with AUCs of 0.78 (95% confidence interval [CI], 0.72-0.83) and 0.75 (95% CI, 0.71-0.78), respectively. The Random Forest model returned an AUC of only 0.53 (95% CI, 0.48-0.59), marginally better than chance alone. Using DCA, the Artificial Neural Network model demonstrated the highest net benefit over the broadest range of threshold probabilities, indicating that it is perhaps better suited for clinical use than the LASSO logistic regression model. Specifically, if only patients with greater than 25% risk of developing HO received prophylaxis, for every 100 patients, use of the Artificial Network Model would result in six fewer patients who unnecessarily receive prophylaxis compared with using the LASSO regression model while not missing any patients who might benefit from it.ConclusionsOur findings suggest that it is possible to risk-stratify combat wounds with regard to eventual HO formation early in the débridement process. Using these data, the Artificial Neural Network model may lead to better patient selection when compared with the LASSO logistic regression approach. Future prospective studies are necessary to validate these findings while focusing on symptomatic HO as the endpoint of interest.Level of evidenceLevel III, prognostic study.

Project description:BackgroundCancer is a major cause of death in children worldwide, and the recorded incidence tends to increase with time. Internationally comparable data on childhood cancer incidence in the past two decades are scarce. This study aimed to provide internationally comparable local data on the incidence of childhood cancer to promote research of causes and implementation of childhood cancer control.MethodsThis population-based registry study, devised by the International Agency for Research on Cancer in collaboration with the International Association of Cancer Registries, collected data on all malignancies and non-malignant neoplasms of the CNS diagnosed before age 20 years in populations covered by high-quality cancer registries with complete data for 2001-10. Incidence rates per million person-years for the 0-14 years and 0-19 years age groups were age-adjusted using the world standard population to provide age-standardised incidence rates (WSRs), using the age-specific incidence rates (ASR) for individual age groups (0-4 years, 5-9 years, 10-14 years, and 15-19 years). All rates were reported for 19 geographical areas or ethnicities by sex, age group, and cancer type. The regional WSRs for children aged 0-14 years were compared with comparable data obtained in the 1980s.FindingsOf 532 invited cancer registries, 153 registries from 62 countries, departments, and territories met quality standards, and contributed data for the entire decade of 2001-10. 385?509 incident cases in children aged 0-19 years occurring in 2·64 billion person-years were included. The overall WSR was 140·6 per million person-years in children aged 0-14 years (based on 284?649 cases), and the most common cancers were leukaemia (WSR 46·4), followed by CNS tumours (WSR 28·2), and lymphomas (WSR 15·2). In children aged 15-19 years (based on 100?860 cases), the ASR was 185·3 per million person-years, the most common being lymphomas (ASR 41·8) and the group of epithelial tumours and melanoma (ASR 39·5). Incidence varied considerably between and within the described regions, and by cancer type, sex, age, and racial and ethnic group. Since the 1980s, the global WSR of registered cancers in children aged 0-14 years has increased from 124·0 (95% CI 123·3-124·7) to 140·6 (140·1-141·1) per million person-years.InterpretationThis unique global source of childhood cancer incidence will be used for aetiological research and to inform public health policy, potentially contributing towards attaining several targets of the Sustainable Development Goals. The observed geographical, racial and ethnic, age, sex, and temporal variations require constant monitoring and research.FundingInternational Agency for Research on Cancer and the Union for International Cancer Control.

Project description:Prior high-trauma fractures identified through health services data are associated with low bone mineral density (BMD) and future fracture risk to the same extent as fractures without high-trauma.IntroductionSome have questioned the usefulness of distinguishing high-trauma fractures from low-trauma fractures. The aim of this study is to compare BMD measurements and risk of subsequent low-trauma fracture in patients with prior high- or low-trauma fractures.MethodsUsing a clinical BMD registry for the province of Manitoba, Canada, we identified women and men age 40 years or older with fracture records from linked population-based healthcare data. Age- and sex-adjusted BMD Z-scores and covariate-adjusted hazard ratios (HR) with 95% confidence intervals (CI) for incident fracture were studied in relation to prior fracture status, categorized as high-trauma if associated with external injury codes and low-trauma otherwise.ResultsThe study population consisted of 64,428 women and men with no prior fracture (mean age 63.7 years), 858 with prior high-trauma fractures (mean age 65.1 years), and 14,758 with prior low-trauma fractures (mean age 67.2 years). Mean Z-scores for those with any prior high-trauma fracture were significantly lower than in those without prior fracture (P < 0.001) and similar to those with prior low-trauma fracture. Median observation time for incident fractures was 8.8 years (total 729,069 person-years). Any prior high-trauma fracture was significantly associated with increased risk for incident major osteoporotic fracture (MOF) (adjusted HR 1.31, 95% CI 1.08-1.59) as was prior low-trauma fracture (adjusted HR 1.55, 95% CI 1.47-1.63), and there was no significant difference between the two groups (prior trauma versus low-trauma fracture P = 0.093). A similar pattern was seen when incident MOF was studied in relation to prior hip fracture or prior MOF, or when the outcome was incident hip fracture or any incident fracture.ConclusionsHigh-trauma and low-trauma fractures showed similar relationships with low BMD and future fracture risk. This supports the inclusion of high-trauma fractures in clinical assessment for underlying osteoporosis and in the evaluation for intervention to reduce future fracture risk.

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Incidence of cancer among U.S. combat casualties: a DoD Trauma Registry study.

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