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贝叶斯基于贝叶斯网络的生存预测模型,用于接受过关口高血压的跨内肝移植系统分流后患者

Rong Chen¹, Ling Luo², Yun-Zhi Zhang¹

¹Department of Infectious Diseases, Second Affiliated Hospital of Chongqing Medical University, Chongqing 400016, China.

World journal of gastroenterology

|April 25, 2024

概括

这项研究开发了一种新的贝叶斯网络模型,用于预测跨内肝移植系统分流 (TIPS) 手术后门高血压 (PHT) 患者的存活率. 该模型准确地识别了影响患者结果的关键因素,帮助治疗策略.

科学领域:

肝病学和胃肠病学肝病学和胃肠学
医疗信息学医疗信息学
生物统计学生物统计学

背景情况:

门性高血压 (PHT),通常是由肝硬化引起的,显著影响患者的生存率.
跨内肝移植系统分流 (TIPS) 对于PHT管理至关重要,但具有肝脏脑病变等风险.
现有的TIPS后生存预后模型缺乏对预后因素相互作用的全面分析.

研究的目的:

开发和验证基于贝叶斯网络 (BN) 的模型,用于预测患有肝硬化诱导的PHT接受TIPS的患者的生存率.
通过考虑预后因素的相互作用来解决当前模型的局限性.

主要方法:

对393名接受PHT TIPS治疗的患者的临床数据进行了回顾性分析.
使用考克斯和最小绝对收缩和选择操作员 (LASSO) 回归的变量选择.
基于BN的2年生存预测模型的构建和评估.

主要成果:

确定的主要生存因素包括年龄,,高血压,TIPS指标,术后门静脉压 (PVP后),肝功能测试 (AST,白血素,前白血素),Child-Pugh等级和MELD得分.
该BN模型显示了高的预测准确度 (0.90),精度 (0.92),回忆 (0.97),和F1得分 (0.95).
在ROC曲线下的面积为0.72,表明模型性能良好.

结论:

成功开发了一种基于BN的强大的生存预测模型,用于TIPS后的PHT患者.
该模型为完善治疗策略和预后评估提供了宝贵的见解.
这种方法增强了对TIPS后PHT患者的生存决定因素的理解.

关键词:

贝叶斯网络是一个贝叶斯网络.肝硬化是肝硬化的一种疾病.门口高血压的高血压.生存预测模型的生存预测模型.跨内肝移植系统的分流.

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