INCIDENCE, ETIOLOGY AND SURGICAL MANAGEMENT OF IATROGENIC URETERIC INJURIES DURING LOW ANTERIOR RESECTION AND COLECTOMY: A HOSPITAL BASED STUDY
DOI:
https://doi.org/10.65605/a-jmrhs.2026.v04.i02.pp130-135Keywords:
Iatrogenic Ureteric Injury, Low Anterior Resection, Colectomy, Ureteral Reconstruction, Colorectal Surgery, Surgical Complications, Urological Trauma.Abstract
OBJECTIVE: To determine the rate, pattern of causes, and outcomes following surgical repair of iatrogenic injury to the ureter during low anterior resection (LAR) and colectomy. MATERIAL AND METHODS: A retrospective cohort study was performed at an academic tertiary hospital from January 2020 to December 2024. Patients who had elective or emergent LAR or colectomy for benign or malignant disease were included. Patient demographics, surgical information, injury type, timing of injury recognition, repair techniques, and complications were obtained from electronic medical records and surgical databases. Chi-square tests, Fisher's exact tests and multivariate logistic regression were used to identify risk factors for injury and complications. A p-value <0.05 was considered statistically significant. RESULTS: 62 ureteric injuries occurred in 1,842 colorectal resections for an overall incidence of 3.36%. The most frequent causes were thermal injury (38.7%), transection (25.8%), ligation (22.6%) and devascularization (12.9%). The injury was discovered intraoperatively in 74.2%. The most common repair was primary repair over a double-J stent (51.6%) and ureteroneocystostomy with or without psoas hitch (29.0%). Complications occurred in 19.4% of cases, with the most common being ureteral stricture (8.1%) and leak (9.7%). CONCLUSION: Ureteric injury during LAR and colectomy is a clinically relevant and apparent complication. Early intraoperative identification, structured urological consultation and injury-specific reconstructive protocols reduce complications. Improved risk assessment, systematic intraoperative ureteral localisation and injury-specific management algorithms are critical for improved clinical outcomes.















