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Updated: Apr 1, 2026

Vessel-sparing Excision and Primary Anastomosis
Published on: January 7, 2019
Comparative Outcomes of Resection: Primary Anastomosis and Hartmann's Procedure in the Management of Sigmoid Volvulus
M M Hossain1, A K M Islam, M Khatun
1Dr Muhammad Moinul Hossain, Junior Consultant, Department of Surgery, Mymensingh Medical College Hospital (MMCH), Mymensingh, Bangladesh;
Abstract:
One major cause of large bowel blockage is sigmoid volvulus, which in more complex instances necessitates surgical intervention. Despite the widespread use of two basic surgical techniques-resection-primary anastomosis and Hartmann's procedure- comparative results in settings with limited resources, such as Bangladesh, are still not well understood. This study compared the outcomes of Hartmann's procedure and resection-primary anastomosis in sigmoid volvulus. From September 2018 to August 2019, the Department of Surgery at Mymensingh Medical College Hospital in Bangladesh was the site of this prospective observational study. A total of 44 patients with sigmoid volvulus were included, with 22 undergoing resection-primary anastomosis and 22 undergoing Hartmann's procedure. Data were collected on patient demographics, clinical and biochemical findings, surgical outcomes and postoperative complications. Statistical analyses were performed using SPSS. Patients in Hartmann's group had higher comorbidities, such as malnutrition (40.91%) and COPD (45.45%) and they were older (57.40±14.65 years vs. 45.90±10.6 years). Anastomotic leaking only happened in the main anastomosis group (13.64%), but gangrenous bowel was more prevalent in the Hartmann's group (27.27%). The primary anastomosis group had a considerably greater rate of re-intervention (22.73%, p=0.02). Only the main anastomosis group (4.55%) experienced mortality. Hartmann's procedure is better suited for high-risk patients, while primary anastomosis offers benefits in stable patients but with a higher risk of complications. Individualized surgical decision-making is crucial to optimizing outcomes in resource-limited settings.
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