A Clinical Parameters-Based Model Predicts Anastomotic Leakage After a Laparoscopic Total Mesorectal Excision: A...

Anastomotic leakage after colorectal surgery is a major and life-threatening complication that occurs more frequently than expected. Intraoperative judgment in predicting potential leakage has shown extremely low sensitivity and specificity. The lack of a model for predicting anastomotic leakage might explain this insufficient judgment. We aimed to propose a clinical parameters-based model to predict anastomotic leakage after laparoscopic total mesorectal excision (TME).This study was a retrospective analysis of a prospectively designed colorectal cancer dataset. In total, 1968 patients with a laparoscopic TME were enrolled from November 1, 2010, to March 20, 2014. The independent risk factors for anastomotic leakage were identified, from which the parameters-based model for leakage was developed.Anastomotic leakage was noted in 63 patients (3.2%). Male sex, a low level of anastomosis, intraoperative blood loss, diabetes, the duration time of the surgery, and low temperature were significantly associated by the bivariate analysis and the Cochran-Mantel-Haenszel test with an increased risk. From these factors, the logistic regression model identified the following 4 independent predictors: male sex (risk ratio [RR] = 1.85, 95% confidence interval [CI]: 1.13-4.87), diabetes (RR = 2.08, 95% CI: 1.19-5.8), a lower anastomosis level (RR = 3.41, 95% CI: 1.17-6.71), and a high volume of blood loss (RR = 1.03, 95% CI: 1.01-1.05). The locally weighted scatterplot smoothing regression showed an anastomosis within 5 cm from the anus and intraoperative blood loss of >100 mL as the cutoff values for a significantly increased risk of leakage. Based on these independent factors, a parameters-based model was established by the regression coefficients. The high and low-risk groups were classified according to scores of 3-5 and 0-2, with leakage rates of 8.57% and 1.66%, respectively (P < 0.001).This parameters-based model could predict the risk of anastomotic leakage following laparoscopic rectal cancer. After further validation, this model might facilitate the intraoperative recognition of high-risk patients to perform defunctional stomas.