Background: Our previous experience with colon injuries suggested that operative decisions based on a defined algorithm improve outcomes. The purpose of this study was to evaluate the validity of this algorithm in the face of an increased incidence of destructive injuries observed in recent years. Study Design: Consecutive patients with full-thickness penetrating colon injuries over an 8-year period were evaluated. Per algorithm, patients with nondestructive injuries underwent primary repair. Those with destructive wounds underwent resection plus anastomosis in the absence of comorbidities or large pre- or intraoperative transfusion requirements (more than 6 units packed RBCs); otherwise they were diverted. Outcomes from the current study (CS group) were compared with those from the previous study (PS group). Results: There were 252 patients who had full-thickness penetrating colon injuries: 150 (60%) patients had nondestructive colon wounds treated with primary repair and 102 patients (40%) had destructive wounds (CS). Demographics and intraoperative transfusions were similar between CS and PS groups. Of the 102 patients with destructive injuries, 75% underwent resection plus anastomosis and 25% underwent diversion. Despite more destructive injuries managed in the CS group (41% vs 27%), abscess rate (18% vs 27%) and colon-related mortality (1% vs 5%) were lower in the CS. Suture line failure was similar in CS compared with PS (5% vs 7%). Adherence to the algorithm was >90% in the CS (similar to PS). Conclusions: Despite an increase in the incidence of destructive colon injuries, our management algorithm remains valid. Destructive injuries associated with pre- or intraoperative transfusion requirements of more than 6 units packed RBCs and/or significant comorbidities are best managed with diversion. By managing the majority of other destructive injuries with resection plus anastomosis, acceptably low morbidity and mortality can be achieved.
- Abdomen Abbreviated Injury Scale
- current study
- packed red blood cells
- previous study
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