Search

Purpose: Numerous studies have modified the Trauma Injury and Severity Score (TRISS) to improve its predictive accuracy for specific trauma populations. The aim of this study was to develop and validate a simple and practical prediction model that accurately predicts mortality for all acute trauma admissions. Methods: This retrospective study used Dutch National Trauma Registry data recorded between 2015 and 2018. New models were developed based on nonlinear transformations of TRISS variables (age, systolic blood pressure (SBP), Glasgow Coma Score (GCS) and Injury Severity Score (ISS)), the New Injury Severity Score (NISS), the sex–age interaction, the best motor response (BMR) and the American Society of Anesthesiologists (ASA) physical status classification. The models were validated in 2018 data and for specific patient subgroups. The models’ performance was assessed based on discrimination (areas under the curve (AUCs)) and by calibration plots. Multiple imputation was applied to account for missing values. Results: The mortality rates in the development and validation datasets were 2.3% (5709/245363) and 2.5% (1959/77343), respectively. A model with sex, ASA class, and nonlinear transformations of age, SBP, the ISS and the BMR showed significantly better discrimination than the TRISS (AUC 0.915 vs. 0.861). This model was well calibrated and demonstrated good discrimination in different subsets of patients, including isolated hip fractures patients (AUC: 0.796), elderly (AUC: 0.835), less severely injured (ISS16) (AUC: 878), severely injured (ISS ≥ 16) (AUC: 0.889), traumatic brain injury (AUC: 0.910). Moreover, discrimination for patients admitted to the intensive care (AUC: s0.846), and for both non-major and major trauma center patients was excellent, with AUCs of 0.940 and 0.895, respectively. Conclusion: This study presents a simple and practical mortality prediction model that performed well for important subgroups of patients as well as for the heterogeneous population of all acute trauma admissions in the Netherlands. Because this model includes widely available predictors, it can also be used for international evaluations of trauma care within institutions and trauma systems.

Objective:To evaluate the impact of the COVID-19 pandemic on the outcome of major trauma patients in the Netherlands. Summary Background Data:Major trauma patients highly rely on immediate access to specialized services, including ICUs, shortages caused by the impact of the COVID-19 pandemic may influence their outcome. Methods:A multi-center observational cohort study, based on the Dutch National Trauma Registry was performed. Characteristics, resource usage, and outcome of major trauma patients (injury severity score ≥16) treated at all trauma-receiving hospitals during the first COVID-19 peak (March 23 through May 10) were compared with those treated from the same period in 2018 and 2019 (reference period).Results:During the peak period, 520 major trauma patients were admitted, versus 570 on average in the pre-COVID-19 years. Significantly fewer patients were admitted to ICU facilities during the peak than during the reference period (49.6% vs 55.8%; P=0.016). Patients with less severe traumatic brain injuries in particular were less often admitted to the ICU during the peak (40.5% vs 52.5%; P=0.005). Moreover, this subgroup showed an increased mortality compared to the reference period (13.5% vs 7.7%; P=0.044). These results were confirmed using multivariable logistic regression analyses. In addition, a significant increase in observed versus predicted mortality was recorded for patients who had a priori predicted mortality of 50% to 75% (P=0.012). Conclusions:The COVID-19 peak had an adverse effect on trauma care as major trauma patients were less often admitted to ICU and specifically those with minor through moderate brain injury had higher mortality rates.

The Berlin poly-trauma definition (BPD) has proven to be a valuable way of identifying patients with at least a 20% risk of mortality, by combining anatomical injury characteristics with the presence of physiological risk factors (PRFs). Severe isolated injuries (SII) are excluded from the BPD. This study describes the characteristics, resource use and outcomes of patients with SII according to their injured body region, and compares them with those included in the BPD.Data were extracted from the Dutch National Trauma Registry between 2015 and 2019. SII patients were defined as those with an injury with an Abbreviated Injury Scale (AIS) score ≥ 4 in one body region, with at most minor additional injuries (AIS ≤ 2). We performed an SII subgroup analysis per AIS region of injury. Multivariable linear and logistic regression models were used to calculate odds ratios (ORs) for SII subgroup patient outcomes, and resource needs.A total of 10.344 SII patients were included; 47.8% were ICU admitted, and the overall mortality was 19.5%. The adjusted risk of death was highest for external (2.5, CI 1.9-3.2) and for head SII (2.0, CI 1.7-2.2). Patients with SII to the abdomen (2.3, CI 1.9-2.8) and thorax (1.8, CI 1.6-2.0) had a significantly higher risk of ICU admission. The highest adjusted risk of disability was recorded for spine injuries (10.3, CI 8.3-12.8). The presence of ≥ 1 PRFs was associated with higher mortality rates compared to their poly-trauma counterparts, displaying rates of at least 15% for thoracic, 17% for spine, 22% for head and 49% for external SII.A severe isolated injury is a high-risk entity and should be recognized and treated as such. The addition of PRFs to the isolated anatomical injury criteria contributes to the identification of patients with SII at risk of worse outcomes.