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Analysis of Risk Factors for Anastomotic Leakage After Laparoscopic Anterior Resection of Rectal Cancer and Construction of a Nomogram Prediction Model

OBJECTIVE: To explore the risk factors of anastomotic leakage (AL) after laparoscopic anterior resection (AR) of rectal cancer and establish a nomogram prediction model. METHODS: Clinical and surgical data of patients who underwent AR of rectal cancer at Sichuan Cancer Hospital from January 2017 to...

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Detalles Bibliográficos
Autores principales: Wang, Keli, Li, Meijiao, Liu, Rui, Ji, Yang, Yan, Jin
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Dove 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9343466/
https://www.ncbi.nlm.nih.gov/pubmed/35928989
http://dx.doi.org/10.2147/CMAR.S364875
Descripción
Sumario:OBJECTIVE: To explore the risk factors of anastomotic leakage (AL) after laparoscopic anterior resection (AR) of rectal cancer and establish a nomogram prediction model. METHODS: Clinical and surgical data of patients who underwent AR of rectal cancer at Sichuan Cancer Hospital from January 2017 to December 2020 were retrospectively collected. Univariate and multivariate logistic regression analyses were used to screen the independent risk factors of AL after AR. A nomogram risk prediction model was established based on the selected independent risk factors and the predictive performance of nomogram was evaluated. RESULTS: A 1013 patients undergoing laparoscopic AR were included, of which 67 had AL, with an incidence of 6.6%. Univariate and multivariate logistic regression analyses showed that male gender, tumors distance from the anus verge of ≤ 5cm, tumors distance from the anus verge of 5–10cm, circumferential tumor growth, operation time ≥ 240min, and no diverting stoma were independent risk factors for AL after AR. A nomogram prediction model was established based on these results. The calibration curve showed that the predicted occurrence probability of the nomogram model was in good agreement with the actual occurrence probability. The area under the receiver operating characteristic (ROC) curve was 0.749. CONCLUSION: The nomogram prediction model based on the independent risk factors of patients undergoing AL after AR can effectively predict the probability of AL.