Diese Publikation ist Teil des DEAL-Vertrags mit Springer.
Zusammenfassung
Introduction
Despite over 50 years of research, trauma remains a significant global health issue. In addition to medical advancements, establishing trauma networks appears to positively impact the survival rates of severely injured patients. The influence of the type of transport (helicopter emergency medical service [HEMS] vs. ground emergency medical service [GEMS]) on mortality depending on the destination hospital in an established trauma network is currently unclear. The objective of the study was to evaluate this line of questioning within the context of an entire trauma network.
Materials and methods
Data from all trauma room patients in the first established trauma network in Germany over a period of 24 months were analyzed. Although the data was collected prospectively and entered the TraumaRegister DGU® database, it was analyzed retrospectively in relation to the research question. The trauma network served a population of approximately 2.3 million people in an area of about 20,000 square kilometers in a predominantly rural area, which comprised 2 Level I, 8 Level II, and 15 Level III hospitals. A 24/7 dual-use helicopter and three other rescue helicopters were available during the day. Two additional rescue helicopters from other networks were potentially available during the night. Patients with an Injury Severity Score (ISS) ≥ 16 were included in this study. Patients with secondary admission, those transferred or discharged within 48 h, and cases with missing Revised Injury Severity Classification II (RISC II) were excluded. Groups were divided according to target hospital level (I, II, or III) and transport type (HEMS or GEMS). A total of 5 groups (LI-H, LI-G, LII-H, LII-G, LIII-G) were available for evaluation, as no patient was transported by helicopter to a Level III hospital during the study period. Univariate statistics were performed using the Chi-Square and Kruskal-Wallis tests. The significance level was set at p < 0.05. Post-hoc analyses were performed for significant results. In addition, multivariate analyses were carried out to identify masked correlations. RISC II was taken to calculate the Standardized Mortality Ratio (SMR).
Results
After applying the inclusion and exclusion criteria, 887 of the 2,596 available cases were included in the study. The distribution to the study groups was as follows: LI-H 20.6% (n = 183), LI-G 17.0% (n = 151), LII-H 21.6% (n = 192), LII-G 35.9% (n = 318), LIII-G 4.8% (n = 43). The univariate analysis of patient characteristics revealed significant differences in seven out of eight variables (Age, Sex, Classification of American Society of Anesthesiologists (ASA), Abbreviated Injury Scale (AIS) of the region head, ISS, New Injury Severity Score (NISS), RISC II). Patients transported to Level I hospitals by HEMS (LI-H group) tended to be younger, have a lower ASA score, and sustain more severe injuries with a high risk of death (RISC II). The evaluation of the preclinical and clinical courses continued to demonstrate the heterogeneity of the patient population, which was characterized by worse vital signs, an increased need for infusion and transfusion, higher intubation rates, longer ventilation times, and longer lengths of stay in ICUs and overall for patients in Level I hospitals, particularly for HEMS transports. Despite these differences, the outcome was comparable. There were no significant differences in mortality between the groups, either unadjusted (LI-H 19,1% (n = 35), LI-G 24,5% (n = 37), LII-H 20,3% (n = 39), LII-G 17,0% (n = 54), LIII-G 14,0% (n = 6), p = 0,326) nor adjusted. Similarly, the multivariate analysis did not reveal any correlations between mortality, hospital level and mode of transportation.
Discussion
While a positive influence on mortality through the formation of trauma networks can be found in literature, the results for the type of transportation are inconsistent. However, there are some indications that HEMS transports may offer a survival advantage. These papers often show rather homogeneous patient characteristics, which were not found in this study. This study demonstrated differentiated prehospital patient selection, in which patients were transported to the appropriate hospital via the most suitable means within a trauma network, ensuring a comparable outcome for all patients. In the future, further optimization and simplification of preclinical patient selection could be achieved by transmitting accident data stored in modern cars that is currently unavailable to emergency services and hospitals.
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