Retrospective Analysis of Risk Factors and Prediction Model of Cervical Anastomotic and Intrathoracic Anastomotic Leakage After Radical Esophagectomy

作者
Yao Wang,Jianning Xu,Jun Qian,Jian Qiu,Min Zhu,Daquan Wang
出处
期刊:Cancer reports [Wiley]
卷期号:8 (9): e70286-e70286
标识
DOI:10.1002/cnr2.70286
摘要

ABSTRACT Background Esophagogastric anastomotic leakage is a common complication after esophageal cancer surgery. Therefore, how to treat and predict is the focus of clinicians' research. Aims To analyze the risk factors of cervical and intrathoracic anastomotic leakage after radical resection of esophageal cancer and establish a prediction model to provide a basis for early clinical prevention and treatment. Methods We retrospectively analyzed the clinical data of 776 esophageal squamous cell carcinoma patients who underwent Sweet ( n =115), Ivor‐Lewis ( n =278), and McKeown (left neck anastomosis) ( n =383) esophagectomy at Yancheng First People's Hospital from August 2019 to December 2021. Univariate and logistic regression models were used to analyze the independent risk factors of anastomotic leakage after esophageal cancer surgery, and a nomogram prediction model was established. Results Of the 776 patients, 95 experienced postoperative anastomotic leakage, with an incidence of 12.2%. There were 63 cases of cervical anastomotic leakage and 32 cases of intrathoracic anastomotic leakage. The multivariate logistic regression analysis showed that BMI, high blood pressure, chronic bronchitis, peptic ulcer, operation way, anastomotic location, and postoperative albumin were independent risk factors for postoperative anastomotic leakage of esophageal cancer ( p < 0.05). Our nomogram prediction model yielded a high predictive value, with an area under the receiver operating characteristic curve of 0.765 (95% CI 0.716–0.814). Conclusion The occurrence of anastomotic leakage after esophageal cancer surgery is related to various factors, including BMI, hypertension, chronic bronchitis, peptic ulcer, operation way, anastomotic way, postoperative albumin, and anastomotic location. The clinical prediction model can promote the early detection, diagnosis, intervention, and treatment of anastomotic leakage and shorten the hospitalization time of patients.
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