Spots Global Cancer Trial Database for Evaluation of AL Prediction for Rectal Cancer

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Trial Identification

Brief Title: Evaluation of AL Prediction for Rectal Cancer

Official Title: Evaluation of a Machine Learning Based Anastomotic Leakage Prediction Model After Anterior Resection for Rectal cancer-a Multicenter, Prospective, Randomized Controlled Study

Study ID: NCT05610904

Conditions

Anastomotic Leak Rectum

Interventions

Prediction model evaluation

Study Description

Brief Summary: Anastomotic leakage is one of the most serious postoperative complications of low rectal cancer, with an incidence of 3%-21%. The occurrence of anastomotic leakage is related to many factors, and the occurrence of anastomotic leakage can be predicted by building a prediction model. Most of the anastomotic leakage prediction models constructed in the past are nomograms, which have limitations in the fitting of model creation. In the previous study, the center took the lead in building a random forest anastomotic leakage prediction model based on machine learning. This study intends to prospectively enroll patients with rectal cancer undergoing anterior abdominal resection and use their clinical data to prospectively verify the efficacy of the anastomotic leakage prediction model, and further improve and promote the prediction model.

Detailed Description: