Diagnosis of bowel and mesenteric injuries in blunt abdominal trauma: a prospective study

Currently, nonoperative management is the procedure of choice for solid organ injury in patients with a blunt abdominal trauma. Missed blunt bowel and mesenteric injuries (BBMIs) are possible because diagnosis is difficult. The aim of our study was to test a new algorithm for BBMI diagnosis using abdominal ultrasonography (AUS), computed tomography (CT), and diagnostic peritoneal lavage (DPL).

We reviewed cases of blunt abdominal injuries over a 10-year period, then we designed an algorithm that was prospectively tested in hemodynamically stable patients over a 2-year period. An abnormal AUS led to helical CT. When the CT showed more than 2 findings suggestive of BBMI, laparotomy was performed. In case of 1 or 2 abnormal CT findings, we performed a DPL and calculated the ratio of white blood cells (WBCs) to red blood cells (RBCs) (WBC/RBC ratio) in the lavage fluid and divided this by the WBC/RBC ratio in peripheral blood. A ratio of 1 or higher was considered positive for BBMI, and a laparotomy was immediately performed. Patients with a ratio of less than 1 were managed nonoperatively.

In the retrospective study, 26 (1%) of 2126 patients admitted to our trauma center for blunt trauma had a BBMI, including 15 (58%) diagnosed after a median delay of 24 hours. In the prospective study, 531 patients were admitted for blunt trauma with multiple injuries, including 131 with abdominal trauma. Computed tomography was performed in 40 patients. There were 2 criteria or more of BBMI in 1 patient, 0 criteria in 27 patients (with an uneventful follow-up), and 1 or 2 criteria in 12 patients who had DPL with a median ratio of 0.82 (ranges, 0.03-9). Five patients had a ratio of 1 or higher. They underwent immediate laparotomy. In all 5 cases, BBMI was found. The 7 patients who had a ratio of less than 1 were observed in ICU and treated for extra-abdominal injuries. No BBMI injury was missed in these patients. The accuracy of the algorithm was 100% (95% confidence interval, 0.99-1.00).

The proposed algorithm (based on AUS, CT, and DPL) had a high accuracy to diagnose BBMI while requiring the performance of DPL in only a few (2%) patients.