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Updated: Jul 6, 2025

The C-seal: A Biofragmentable Drain Protecting the Stapled Colorectal Anastomosis from Leakage
Published on: November 4, 2010
Clinical risk factors and Risk assessment model for Anastomotic leakage after Rectal cancer resection
1Department of Gastrointestinal Surgery, The Fifth Affiliated Hospital of Sun Yat-Sen University, Zhuhai, Guangdong, China.
Background:
Anastomotic leakage (AL) is the most serious complication after rectal cancer surgery. Risk factors associated with AL have been documented in previous studies; however, the consensus is still lacking. In this retrospective study, we aimed to identify risk factors for AL after rectal cancer resection and to create an accurate and effective tool for predicting the risk of this complication.
Methods:
The study cohort comprised of 276 patients with rectal cancer who had undergone anterior resection between 2015 and 2020. Twenty-four selected variables were assessed by univariate and multivariate logistic regression analyses to identify independent risk factors of AL. A risk assessment model for predicting the risk of AL was established on the basis of the regression coefficients of each identified independent risk factor.
Results:
Anastomotic leakage occurred in 20 patients (7.2%, 20/276). Multivariate analysis identified the following variables as independent risk or protective factors of AL: perioperative ileus ( P < 0.001, odds ratio [OR] = 14.699), tumor size ≥5 cm ( P = 0.025, OR = 3.925), distance between tumor and anal verge <7.5 cm ( P = 0.045, OR = 3.512), obesity ( P = 0.032, OR = 7.256), and diverting stoma ( P = 0.008, OR = 0.143). A risk assessment model was constructed and patients were allocated to high-, medium-, and low-risk groups on the basis of risk model scores of 5-7, 2-4, and 0-1, respectively. The incidences of AL in these three groups were 61.5%, 11.9%, and 2.0%, respectively ( P < 0.001).
Conclusions:
Our risk assessment model accurately and effectively identified patients at high risk of AL and could be useful in aiding decision-making aimed at minimizing adverse outcomes associated with leakage.
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