Suppr超能文献

基于贝叶斯网络模型的全胃切除术后食管空肠吻合口漏危险因素分析

Analysis of risk factors for esophagojejunal anastomotic leakage after total gastrectomy based on Bayesian network model.

作者信息

Wang Yun-Feng, Guo Zi-Qi, Han Jing-Xiang, Gao Lin-Na, Liu Yu-Ming, Jia Kai, Chen Hao, Yao Tian, Huang He

机构信息

The First Clinical Medical College, Shanxi Medical University, Taiyuan, Shanxi, China.

Department of Gastrointestinal Surgery, First Hospital of Shanxi Medical University, Taiyuan, Shanxi, China.

出版信息

Front Med (Lausanne). 2025 Aug 5;12:1632214. doi: 10.3389/fmed.2025.1632214. eCollection 2025.

Abstract

OBJECTIVES

This research aims to develop a nomogram for predicting esophagojejunal anastomotic leakage (EJAL) after total gastrectomy and analyze the relationship between individual risk factors through the Bayesian network model.

MATERIALS AND METHODS

The research enrolled 238 patients who underwent total gastrectomy and esophagojejunal Roux-en-Y anastomosis for gastric cancer between January 2017 and June 2022 in the Department of Gastrointestinal Surgery of the First Hospital of Shanxi Medical University and retrospectively collected clinical data of the patients. Multivariable logistic regression was used to explore the risk factors of EJAL and a nomogram based on the results was constructed. The predictive ability of the model was assessed by receiver operating characteristic (ROC) curve and calibration curve. In addition, the clinical benefit was indicated by decision curve analysis (DCA). Ultimately, a Bayesian network model was developed to analyze the interrelationship between the risk factors.

RESULTS

Esophagojejunal anastomotic leakage occurred in 13 of 238 patients (5.4%). End-to-side anastomosis, diabetes mellitus (DM), preoperative albumin (ALB) ≤ 33.6 g/L, drinking history and systemic inflammation response index (SIRI) > 1.18 were identified as independent risk factors for EJAL based on multivariable logistic regression. A nomogram containing the aforementioned factors was constructed, with an area under the receiver operating characteristic curve (AUROC) of 0.880. Likewise, the model showed good predictive ability and clinical application in the calibration curve and DCA. Ultimately, the Bayesian network model demonstrates that type of anastomosis (ToA), DM, and ALB were directly associated with EJAL development, while gender, age, drinking history, smoking history, hypertension, and SIRI were conditionally dependent on EJAL given the presence of mediator variables.

CONCLUSION

Surgeons should be alert to the occurrence of EJAL, especially in patients with end-to-side anastomosis, DM, drinking history, preoperative lower ALB, and higher SIRI. Also, males, advanced age, smoking history, and hypertension can affect the development of EJAL.

摘要

目的

本研究旨在制定一种用于预测全胃切除术后食管空肠吻合口漏(EJAL)的列线图,并通过贝叶斯网络模型分析个体危险因素之间的关系。

材料与方法

本研究纳入了2017年1月至2022年6月在山西医科大学第一医院胃肠外科接受胃癌全胃切除及食管空肠Roux-en-Y吻合术的238例患者,并回顾性收集了患者的临床资料。采用多变量逻辑回归分析EJAL的危险因素,并根据结果构建列线图。通过受试者工作特征(ROC)曲线和校准曲线评估模型的预测能力。此外,决策曲线分析(DCA)表明了临床获益情况。最终,建立了贝叶斯网络模型来分析危险因素之间的相互关系。

结果

238例患者中有13例发生食管空肠吻合口漏(5.4%)。基于多变量逻辑回归分析,端侧吻合、糖尿病(DM)、术前白蛋白(ALB)≤33.6 g/L、饮酒史和全身炎症反应指数(SIRI)>1.18被确定为EJAL的独立危险因素。构建了包含上述因素的列线图,受试者工作特征曲线下面积(AUROC)为0.880。同样,该模型在校准曲线和DCA中显示出良好的预测能力和临床应用价值。最终,贝叶斯网络模型表明吻合方式(ToA)、DM和ALB与EJAL的发生直接相关,而性别、年龄、饮酒史、吸烟史、高血压和SIRI在存在中介变量的情况下与EJAL有条件相关。

结论

外科医生应警惕EJAL的发生,尤其是在进行端侧吻合、患有DM、有饮酒史、术前ALB较低和SIRI较高的患者中。此外,男性、高龄、吸烟史和高血压会影响EJAL的发生。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8ebd/12361184/c17ad2253d1f/fmed-12-1632214-g001.jpg

文献检索

告别复杂PubMed语法,用中文像聊天一样搜索,搜遍4000万医学文献。AI智能推荐,让科研检索更轻松。

立即免费搜索

文件翻译

保留排版,准确专业,支持PDF/Word/PPT等文件格式,支持 12+语言互译。

免费翻译文档

深度研究

AI帮你快速写综述,25分钟生成高质量综述,智能提取关键信息,辅助科研写作。

立即免费体验