Comparing trauma mortality of injured patients in India and the USA: a risk-adjusted analysis

ObjectivesComparisons of risk-adjusted trauma mortality between high-income countries and low and middle-income countries (LMICs) can be used to identify specific patient populations and injury patterns for targeted interventions. Due to a paucity of granular patient and injury data from LMICs, there is a lack of such comparisons. This study aims to identify independent predictors of trauma mortality and significant differences between India and the USA.MethodsA retrospective cohort study of two trauma databases was conducted. Demographic, injury, physiologic, anatomic and outcome data were analyzed from India’s Towards Improved Trauma Care Outcomes project database and the US National Trauma Data Bank from 2013 to 2015. Multivariate logistic regression analyses were performed to determine significant independent predictors of mortality.Results687 407 adult trauma patients were included (India 11 796; USA 675 611). Patients from India were significantly younger with greater male preponderance, a higher proportion presented with physiologic abnormalities and suffered higher mortality rates (23.2% vs. 2.8%). When controlling for age, sex, physiologic abnormalities, and injury severity, sustaining an injury in India was the strongest predictor of mortality (OR 13.85, 95% CI 13.05 to 14.69). On subgroup analyses, the greatest mortality difference was seen in patients with lower Injury Severity Scores.ConclusionAfter adjusting for demographic, physiologic abnormalities, and injury severity, trauma-related mortality was found to be significantly higher in India. When compared with trauma patients in the USA, the odds of mortality are most notably different among patients with lower Injury Severity Scores. While troubling, this suggests that relatively simple, low-cost interventions focused on standard timely trauma care, early imaging, and protocolized treatment pathways could result in substantial improvements for injury mortality in India, and potentially other LMICs.Level of evidenceLevel 3, retrospective cohort study.

An Overview of Amish Mortalities at a Level I Trauma Center

Background The Amish population is a unique subset of patients that may require a specialized approach due to their lifestyle differences compared to the general population. With this reasoning, Amish mortalities may differ from typical trauma mortality patterns. We sought to provide an overview of Amish mortalities and hypothesized that there would be differences in injury patterns between mortalities and survivors. Methods All Amish trauma patients who presented and were captured by the trauma registry at our Level I trauma center over 20 years (1/2000-2004/2020) were analyzed. A retrospective chart review was subsequently performed. Patients who died were of interest to this study. Demographic and clinical variables were analyzed for the mortalities. Mortalities were then compared to Amish patients who survived. Results There were 1827 Amish trauma patients during the study period and, of these, 32 (1.75%) were mortalities. The top 3 mechanisms of injury leading to mortality were falls (34.4%), pedestrian struck (21.9%), and farming accidents (15.6%). Pediatric (age ≤ 14y) (25%) and geriatric (age ≥ 65y) (28.1%) had the highest percentage of mortalities. Mortalities in the Amish population were significantly older (mean age: 39 years vs 27 years, P = .003) and had significantly higher ISS (mean ISS: 29 vs 10, P < .001) compared to Amish patients who survived. Discussion The majority of mortalities occurred in the pediatric and geriatric age groups and were falls. Further intervention and outreach in the Amish population should be done to highlight this particular cause of mortality. Level of Evidence Level III, epidemiological.

Association Between Health Insurance and Race With Mortality From Trauma: a Retrospective Study

Background: The population health implications of the growing burden of trauma-related mortality may be influenced by access to health insurance coverage, and demographic characteristics such as race and ethnicity. We investigated the effects of health insurance status and race/ethnicity on the risk of mortality among trauma victims in Texas.Methods: Using Texas trauma registry data from 2014 - 2016, we categorized health insurance coverage into private, public, and uninsured, and categorized patients with serious injuries into Non-Hispanic Whites, Non-Hispanic Blacks, Hispanics Any-Race, and Others. Multivariate logistic regression was used to estimate the effects of health insurance status and race/ethnicity on mortality, controlling for age, gender, severity of the trauma, cause of trauma, presence of comorbid conditions, trauma center designation, presence of a traumatic brain injury (TBI), and severity of a TBI. Results: From January 1, 2014, to December 31, 2016, there were 415,159 trauma cases in Texas; 8,827 (2.1%) were fatal. Among patients with at least a moderate injury, 24, 606 (17.4%) were uninsured, and 98, 237 (69.4%) identified as Non-Hispanic White. In the multivariate analysis, Hispanics of any race and Non-Hispanic Blacks had higher adjusted odds of trauma mortality compared to Non-Hispanic Whites [ORHispanics= 1.25: 95% CI (1.16 – 1.36)] [ORBlacks= 2.11: 95% CI (1.87 – 2.37)]. Similarly, compared to privately insured, uninsured patients had 86% higher odds of trauma-related death [OR= 1.86: 95% CI (1.66 – 2.05)]. The effects of lack of health insurance on trauma mortality varied across race/ethnicity of the victims; uninsured Non-Hispanic Blacks had disproportionately higher adjusted odds of trauma mortality than uninsured Whites. Conclusion: Using Texas trauma registry data, we found significant disparities in trauma-related mortality risk based on race/ethnicity and health insurance coverage. The identification of trauma mortality inequalities could inform the design and implementation of future public health interventions.