Prevalence and Risk Factors for Anastomotic Leakage of Intestinal Anastomosis in Yekatit 12 Hospital Medical College, Addis Ababa, Ethiopia: A Cross-sectional Study
Abstract
iBackground:/i An anastomotic leak (AL) is a serious complication of gastrointestinal surgery, characterized by a loss of integrity at the anastomotic site. Despite advancements in gastrointestinal surgery, AL remains a leading cause of postoperative mortality and morbidity worldwide. iObjective:/i To determine prevalence and identify associated factors of AL following intestinal resection and anastomosis. iMethods:/i A cross-sectional study was conducted on 103 patients who underwent intestinal anastomosis at Yekatit 12 Hospital Medical College from October 2022 to July 2024. Data were collected retrospectively from patient records and analyzed using SPSS version 26. Descriptive statistics, binary logistic regression, and multivariate analysis were performed. A p-value 0.05 was considered statistically significant. iResults:/i The prevalence of AL was 13.6%. Gastrointestinal (GI) contamination during the procedure demonstrated a statistically significant association with AL (AOR = 8.88, 95% CI: 1.74–45.31, p=0.009). The median postoperative hospital stay was 8 days for the entire cohort but 21.5 days for patients with AL. The AL-related mortality rate was 28.6%. iConclusion:/i The prevalence of AL in this study was higher than previously reported in other Ethiopian studies. GI contamination was a significant independent risk factor for AL, which was associated with prolonged hospitalization and high mortality. Meticulous surgical technique to minimize contamination is crucial to prevent AL and its severe consequences.
Key Points
Objective
This study aims to determine the prevalence of anastomotic leakage and identify its associated risk factors following intestinal surgery.
Methods
- Conducted a cross-sectional study with 103 patients who underwent intestinal anastomosis.
- Data collected retrospectively from patient records.
- Analyzed data using SPSS version 26 with descriptive statistics and binary logistic regression.