Does the time of the day affect multiple trauma care in hospitals? A retrospective analysis of data from the TraumaRegister DGU®

The TraumaRegister DGU® is a multicenter database with the aim of pseudonymized and standardized documentation of severely injured patients. The database of the German Trauma Society (Deutsche Gesellschaft für Unfallchirurgie, DGU) was founded in 1993. Data included in the TraumaRegister DGU® are collected prospectively. Patients with an admission to the hospital via trauma center with subsequent admission to ICU/ICM (intensive care unit/intermediate care medicine) or death after arrival at the hospital and before admission to the ICU were included. Information on demographics; the injury pattern; comorbidities; pre- and in-hospital management; the clinical course during treatment in the ICU (intensive care unit); relevant laboratory findings, including data on transfusions; and outcomes are documented in the register. The AUC - Academy for Trauma Surgery (AUC - Akademie der Unfallchirurgie GmbH) provided the infrastructure for documentation, data management and data analysis. The Committee on Emergency Medicine, Intensive Care and Trauma Management (Sektion NIS) of the German Trauma Society provides scientific leadership. Pseudonymized data of participating hospitals are submit to a central database via web-based application. Most of the participating hospitals are located in Germany, but an increased number of hospitals in other countries contribute data as well. Currently, approximately 30,000 cases from more than 650 hospitals are entered into the database per year.

TraumaNetzwerk DGU® aims to improve the quality and reliability of care for severely injured individuals nationwide.

Trauma networks are formed to guarantee high-quality medical care for multiple trauma patients.

The requirements for a trauma network are the existence of one supra-regional trauma center, 2 regional trauma centers and 3 local trauma centers and the implementation of guidelines for trauma patients with special injuries such as spinal cord injuries or burns. The Whitebook Medical Care of the Severely Injured [18] provides detailed information about the functions of the supra-regional, regional and local trauma centers within a trauma network. The equipment, staff and facilities are defined. The centers are classified in the TraumaNetzwerk DGU® according to the level of care (level I, II and III) within the German health care system [19].

The present study is in line with the publication guidelines of the TraumaRegister DGU® and was registered as TR-DGU project ID 2018–001 N. The Ethics Committee Kiel, Schleswig-Holstein, examined and approved the study (AZ D527/18).

A total of 58,939 trauma patients were evaluated from 2007 to 2017, and the data were analyzed retrospectively. Only data documented in the TraumaRegister DGU® were analyzed.

Not all patient data were available for all analyses. If the data were incomplete for a given evaluation, that patient was excluded from that analysis. The worst injury was considered an Abbreviated Injury Scale (AIS) score of 3 or higher (MAIS 3+). All data were taken from TraumaRegister DGU®. All patients between 1 and 100 years old with a primary admission and documented time of admission were included. Secondary admissions were excluded. We included all participating hospitals within Germany. Approximately 585 hospitals were included.

A day was divided into four time periods: 6.00 am–11.59 am (morning) (n = 14,496 patients), 12.00 pm–5.59 pm (afternoon) (n = 24,226 patients), 6.00 pm–11.59 pm (evening) (n = 16,278 patients), and 0.00 am–5.59 am (night) (n = 3939 patients). Trauma patients were grouped according to their time of admission. Patients who arrived at the hospital between 6.00 and 11.59 am composed the morning group. Trauma patients with an arrival time of 12.00 pm were added to the afternoon group. In the following analyses, we differentiated between day (6.00 am- 11.59 am, 12.00 pm- 5.59 pm) and night (6.00 pm–11.59 pm, 0.00 am–5.59 am).

Statistical analyses were performed with SPSS 24.0. (IBM, Armonk, NY, USA) and GraphPad Prism 7 (GraphPad Software, Inc., USA). For descriptive analyses, the results are presented as the means ± standard deviations (SDs). For comparison of means ± standard deviations, we used one-way ANOVA. Differences in the proportions between groups were tested using the chi-squared test. To compare results across different time groups, we used the Kruskal-Wallis test. The unpaired t-test with Welch’s correction was used to calculate the mean values and SDs. The data are presented as the means and SDs for continuous measurements and as numbers (percentages) for categorical variables. Statistical significance was defined as p < 0.05. The large sample size resulted in very small p-values; thus, the p-values should be interpreted with caution. In addition to statistical significance, the clinical relevance of the observed differences always needs to be considered.

A logistic regression analysis of the outcomes in multiple trauma patients was used to identify the influencing factors. The important variables included the RISC II score (a combination of 13 different factors) [20], trauma center level, time of day, year of trauma, and the performance of whole-body multislice CT. The RISC II score was chosen as a predictor of mortality because it had a significantly larger area under the ROC curve (AUROC) than the other predictors [20]. In the development data set, the discrimination of the RISC II score, as reflected in the AUROC, was 0.947 (0.944–0.951) when all available data were included [20]. The AUROC in this study was: 0.939 (95% CI 0.936–0.941).

The regression coefficient B was determined as a statistical measure of the average functional relationship between the dependent and independent variables. The standard error represents the average distance that the observed values fall from the regression line, and Exp (B) is the exponentiation of the B coefficient, which is an odds ratio. Odds ratios are presented with their respective 95% confidence intervals.

Different clinical parameters of the trauma patients were evaluated to identify substantial differences between patients admitted during the day and those admitted at night (Table 1). The most common causes of injury in patients during all admission periods were car accidents and low falls (< 3 m) (Table 1). Among patients admitted at night, the percentages admitted due to car accidents and low falls were the highest. Motorcycle and pedestrian accidents accounted for the greatest percentages of admissions between 6.00 pm and 11.59 pm (p < 0.0001).

The percentage of male trauma patients was higher than the percentage of female trauma patients in all evaluated time periods and days.

Severe trauma patients admitted at night were significantly younger than those admitted during the day (p < 0.0001) (Table 1). Among the patients admitted at night, the mean age was 49.4 ± 22.8 years (p < 0.0001).

The mean injury severity score (ISS) was higher in patients admitted in the evening (21.0 ± 11.6) and at night (21.4 ± 11.5) (Table 1) than in those admitted at other times.

The lowest mean Glasgow coma scale (GCS) scores were identified in the patients admitted in the evening (12.0 ± 4.3) and at night (11.5 ± 4.4). Patients admitted at night had the highest percentage with an AIS score ≥ 3 for head injuries (Table 1).

The highest proportion of patients with an AIS score ≥ 3 for thoracic injuries was identified in those admitted in the afternoon, with 12,317 patients (50.8%) (Table 1). The highest proportions of patients with an AIS score ≥ 3 for abdominal injuries were identified in those admitted at night, with 502 patients (12.7%), and in the morning, with 1807 patients (12.5%) (Table 1).

We evaluated the percentages of trauma patients who were treated in level I, level II and level III trauma centers. The majority of the patients [51,495 patients (59.6%)] were admitted to level I trauma centers. A total of 26,576 patients were admitted to level II centers (30.7%), and 8369 patients (9.7%) were admitted to level III trauma centers.

Time plays an important role in multiple trauma management (Table 2). A longer out-of-hospital time was found for patients admitted during the evening and at night (63.8 min, 65.5 min) than for those admitted during the day (Table 2). Interestingly, the longest waiting time in the emergency room occurred in the morning and not at night.

The longest interval from arrival at the emergency room to the performance of a CT scan occurred at night (Table 2). The time between arrival and the performance of an X-ray was also evaluated, and the longest intervals occurred in the morning (16.8 min) and at night (16.2 min) (Table 2). The length of hospital stay and days in the ICU showed slight variations (Table 2).

We also evaluated differences among trauma centers of varying levels during different time periods. The majority of multiple trauma patients were treated in level I hospitals (51,495 patients, 59.6%). A total of 26,576 patients (30.7%) were examined in level II centers, and 8369 patients (9.7%) were examined in level III centers. The majority of patients were treated in level I trauma centers independent of the time of the day.

The patients treated at the three levels of trauma centers had significant differences in injury severity, with the highest mean ISS identified in patients treated at level I centers and the lowest ISS identified in patients treated at level III trauma centers (Table 3). Unlike among patients treated at level II and III trauma centers, those treated at level I trauma centers did not differ significantly in their ISS based on whether they were treated during the day or at night.

The time until imaging was performed was longer in level III trauma centers than in level I or II trauma centers at all times. Differences between the levels of trauma centers increased slightly at night.

We evaluated the times between hospital admission and the performance of a CT scan and admission and the performance of an emergency operation (Table 3). The time until the CT scan was longer in level III trauma centers than in level I and II trauma centers. The shortest time to the performance of a CT scan was found in level I trauma centers during all time periods. We found the longest time to imaging at night in all trauma centers (level I: 21.9 min, level II: 27.0 min, level III: 33.3 min). Emergency operations were defined as operations performed after or during the initial assessment due to life-threatening injuries. The time interval until imaging did not delay the time until emergency operation in different levels of trauma centers.

With regard to survival, we focused on the predicted (RISC II score) and observed mortality in different time intervals. The RISC II score and mortality were correlated in all time intervals. We found the highest mortality rate of 15.7% at night (95% confidence interval 14.6–16.9), when the predicted mortality was 14.5%. A relatively higher than predicted mortality rate was also observed in the morning (14.3, 95% confidence interval 13.7 and 14.9). The predicted mortality based on the RISC II score was 13.4% (Table 4). The mortality rate was significantly lower in the afternoon (12.9, 95% confidence interval 12.5–13.3, predicted mortality: 12.4%) than at night (15.7%; 95% confidence interval 14.6–16.9, predicted mortality: 14.5%).

A logistic regression analysis of mortality was performed to identify the factors influencing the mortality rate in multiple trauma patients. The odds ratio and regression coefficient varied during different time periods within a day. The RISC II score, performance of a CT scan and level of trauma center were known predictors. The year was adjusted for in the model. An effect of the time of arrival on the mortality rate was not observed (Table 5).