Physician-led prehospital management is associated with reduced mortality in severe blunt trauma patients: a retrospective analysis of the Japanese nationwide trauma registry

Impact of physician-staffed ground emergency medical services-administered pre-hospital trauma care on in-hospital survival outcomes in Japan

PURPOSE

In Japan, the vehicle used in pre-hospital trauma care systems with physician-staffed ground emergency medical services (GEMS) is referred to as a "doctor car". Doctor cars are highly mobile physician-staffed GEMS that can provide complex pre-hospital trauma management using various treatment strategies. The number of doctor car operations for patients with severe trauma has increased. Considering facility factors, the association between doctor cars and patient outcomes remains unclear. Therefore, this study aimed to examine the relationship between doctor cars for patients with severe trauma and survival outcomes in Japan.

METHODS

A nationwide retrospective cohort study was conducted to compare the impact of the doctor car group with the non-physician-staffed GEMS group on in-hospital survival in adult patients with severe trauma. The data were analyzed using multivariable logistic regression models with generalized estimating equations.

RESULTS

This study included 372,365 patients registered in the Japan Trauma Data Bank between April 2009 and March 2019. Of the 49,144 eligible patients, 2361 and 46,783 were classified into the doctor car and non-physician staffed GEMS groups, respectively. The adjusted odds ratio (OR) for survival was significantly higher in the doctor car group than in the non-physician staffed GEMS group (adjusted OR = 1.228 [95% confidence interval 1.065-1.415]).

CONCLUSION

Using nationwide data, this novel study suggests that doctor cars improve the in-hospital survival rate of patients with severe trauma in Japan. Therefore, doctor cars could be an option for trauma strategies.

Brief Comparative Analysis of Trauma Care Specialties in Europe and the United States

Understanding the variation in training and nuances of trauma provider practice between the countries in Europe and the United States is a daunting task. This article briefly reviews the key specialties of trauma care in Europe including emergency medical services (EMS), emergency medicine, anesthesia, trauma surgery, and critical care. The authors hope to inform U.S. military clinicians and medical planners of the major differences in emergency and trauma care that exist across Europe. Emergency medicine exists as both a primary specialty and a subspecialty across Europe, with varying stages of development as a specialty in each country. There is heavy physician involvement in EMS in much of Europe, with anesthesiologists having additional EMS training typically providing prehospital critical care. Because of the historical predominance of blunt trauma in Europe, in many countries, trauma surgery is a subspecialty with initial orthopedic surgery training versus general surgery. Intensive care medicine has various training pathways across Europe, but there have been great advances in standardizing competency requirements across the European Union. Finally, the authors suggest some strategies to mitigate the potential negative consequences of joint medical teams and how to leverage some key differences to advance life-saving medical interoperability across the North Atlantic Treaty Organization alliance.

Clinical application of a body area network-based smart bracelet for pre-hospital trauma care

Objective

This study aims to explore the efficiency and effectiveness of a body area network-based smart bracelet for trauma care prior to hospitalization.

Methods

To test the efficacy of the bracelet, an observational cohort study was conducted on the clinical data of 140 trauma patients pre-admission to the hospital. This study was divided into an experimental group receiving smart bracelets and a control group receiving conventional treatment. Both groups were randomized using a random number table. The primary variables of this study were as follows: time to first administration of life-saving intervention, time to first administration of blood transfusion, time to first administration of hemostatic drugs, and mortality rates within 24 h and 28 days post-admission to the hospital. The secondary outcomes included the amount of time before trauma team activation and the overall length of patient stay in the emergency room.

Results

The measurement results for both the emergency smart bracelet as well as traditional equipment showed high levels of consistency and accuracy. In terms of pre-hospital emergency life-saving intervention, there was no significant statistical difference in the mortality rates between both groups within 224 h post-admission to the hospital or after 28-days of treatment in the emergency department. Furthermore, the treatment efficiency for the group of patients wearing smart bracelets was significantly better than that of the control group with regard to both the primary and secondary outcomes of this study. These results indicate that this smart bracelet has the potential to improve the efficiency and effectiveness of trauma care and treatment.

Conclusion

A body area network-based smart bracelet combined with remote 5G technology can assist the administration of emergency care to trauma patients prior to hospital admission, shorten the timeframe in which life-saving interventions are initiated, and allow for a quick trauma team response as well as increased efficiency upon administration of emergency care.

Multifaceted Analysis of the Environmental Factors in Severely Injured Trauma: A 30-Day Survival Analysis

(1) Background: Most factors that predict the in-hospital survival rate in patients with severe trauma are patient-related factors; environmental factors are not currently considered important. Predicting the severity of trauma using environmental factors could be a reliable and easy-to-use method. Therefore, the purpose of this study was to determine whether environmental factors affect the survival in patients with severe trauma. (2) Methods: Medical records of patients who activated trauma team in the single regional trauma center, from 2016 to 2020, were retrospectively analyzed. After exclusion of young patients (<19 years old), cases of mild trauma (ISS < 16), and non-preventable deaths (trauma and injury severity score <25%), a total of 1706 patients were included in the study. (3) Results: In the Cox proportional hazard regression analysis, older age, night compared with day, and high rainfall were identified as statistically significant environmental predictors of mortality due to severe trauma. The relationship between mortality and precipitation showed a linear relationship, while that between mortality and temperature showed an inverted U-shaped relationship. (4) Conclusions: Various environmental factors of trauma affect mortality in patients with severe trauma. In predicting the survival of patients with severe trauma, environmental factors are considered relatively less important, though they can be used effectively.

Validation of the Trauma and Injury Severity Score for Prediction of Mortality in a Greek Trauma Population

BACKGROUND

Although the Trauma and Injury Severity Score (TRISS) has been extensively used for mortality risk adjustment in trauma, its applicability in contemporary trauma populations is increasingly questioned.

OBJECTIVE

The study aimed to evaluate the predictive performance of the TRISS in its original and revised version and compare these with a recalibrated version, including current data from a Greek trauma population.

METHODS

This is a retrospective cohort study of admitted trauma patients conducted in two tertiary Greek hospitals from January 2016 to December 2018. The model algorithm was calculated based on the Major Trauma Outcome Study coefficients (TRISSMTOS), the National Trauma Data Bank coefficients (TRISSNTDB), and reweighted coefficients of logistic regression obtained from a Greek trauma dataset (TRISSGrTD). The primary endpoint was inhospital mortality. Models' prediction was performed using discrimination and calibration statistics.

RESULTS

A total of 8,988 trauma patients were included, of whom 854 died (9.5%). The TRISSMTOS displayed excellent discrimination with an area under the curve (AUC) of 0.912 (95% CI 0.902-0.923) and comparable with TRISSNTDB (AUC = 0.908, 95% CI 0.897-0.919, p = .1195). Calibration of both models was poor (Hosmer-Lemeshow test p < .001), tending to underestimate the probability of mortality across almost all risk groups. The TRISSGrTD resulted in statistically significant improvement in discrimination (AUC = 0.927, 95% CI 0.918-0.936, p < .0001) and acceptable calibration (Hosmer-Lemeshow test p = .113).

CONCLUSION

In this cohort of Greek trauma patients, the performance of the original TRISS was suboptimal, and there was no evidence that it has benefited from its latest revision. By contrast, a strong case exists for supporting a locally recalibrated version to render the TRISS applicable for mortality prediction and performance benchmarking.