A nomogram predicting the need for bleeding interventions after high-grade renal trauma: Results from the American Association for the Surgery of Trauma Multi-institutional Genito-Urinary Trauma Study (MiGUTS)

BACKGROUND The management of high-grade renal trauma (HGRT) and the indications for intervention are not well defined. The American Association for the Surgery of Trauma (AAST) renal grading does not incorporate some important clinical and radiologic variables associated with increased risk of interventions. We aimed to use data from a multi-institutional contemporary cohort to develop a nomogram predicting risk of interventions for bleeding after HGRT. METHODS From 2014 to 2017, data on adult HGRT (AAST grades III-V) were collected from 14 level 1 trauma centers. Patients with both clinical and radiologic data were included. Data were gathered on demographics, injury characteristics, management, and outcomes. Clinical and radiologic parameters, obtained after trauma evaluation, were used to predict renal bleeding interventions. We developed a prediction model by applying backward model selection to a logistic regression model and built a nomogram using the selected model. RESULTS A total of 326 patients met the inclusion criteria. Mechanism of injury was blunt in 81%. Median age and injury severity score were 28 years and 22, respectively. Injuries were reported as AAST grades III (60%), IV (33%), and V (7%). Overall, 47 (14%) underwent interventions for bleeding control including 19 renal angioembolizations, 16 nephrectomies, and 12 other procedures. Of the variables included in the nomogram, a hematoma size of 12 cm contributed the most points, followed by penetrating trauma mechanism, vascular contrast extravasation, pararenal hematoma extension, concomitant injuries, and shock. The area under the receiver operating characteristic curve was 0.83 (95% confidence interval, 0.81-0.85). CONCLUSION We developed a nomogram that integrates multiple clinical and radiologic factors readily available upon assessment of patients with HGRT and can provide predicted probability for bleeding interventions. This nomogram may help in guiding appropriate management of HGRT and decreasing unnecessary interventions.