An Algorithm to Avoid Missed Bowel Injuries in Blunt Abdominal Trauma Patients

Bowel injuries following blunt abdominal trauma (BAT) are evasive to detect clinically and with current imaging modalities. These injuries require immediate recognition and operative intervention. Short diagnostic delays can result in significant morbidity and mortality. The goal of this study was to develop a point-based scoring system for the detection of bowel injuries in BAT in order to decrease the incidence of missed and delayed bowel injury diagnoses and to guide clinical decision-making. Methods: A unique scoring system based on imaging, physical exam findings, and laboratory values that awards points for findings suggestive of bowel injury was created. The AMBI algorithm was implemented at a Level I trauma center for a 9-month trial period for adult BAT patients. Results: A total of 141 patients with BAT were evaluated using the AMBI algorithm during the study period. Hospital length of stay (HLOS) decreased from 15 days (IQR 6-31.5) to 6 days (IQR 3-10) (P = 0.0152) for patients scored with AMBI. Patients with an AMBI score of ≥1.5 were significantly more likely to have bowel injury during hospitalization following traumatic injury than those with an AMBI score <1.5 (OR 262; 95% CI, 31.7-2785; P < 0.0001). AMBI was more sensitive for predicting bowel injury than two previously published scoring systems for detecting bowel injury. Conclusions: The AMBI score helped to detect bowel injuries for BAT patients. These patients also had a decreased HLOS. Future refinement of this scoring system is needed, including expanding to other institutions and integration with artificial intelligence programs.