活体捐赠移植后预测早期功能的一种手术前的诺姆图和基于网络的临床决策支持系统:一项回顾性多中心队列研究
Jayeon Ahn1, Minyu Kang2, Sangwan Kim1,3
1Department of Surgery, Seoul National University College of Medicine, Seoul, Republic of Korea.
International journal of surgery (London, England)
|November 17, 2025
概括
这项研究开发了一种实用模型,用于预测活体捐赠者移植 (LDKT) 后的早期功能恢复. 该模型使用了基本的移植前数据,并经过验证,提供了有用的临床决策工具.
科学领域:
- 腎臟病學 (nephrology) 是一種醫學專業.
- 移植医学 移植医学
- 医疗信息学 医疗信息学
背景情况:
- 早期移植后的功能对于接受移植的患者的长期结果至关重要.
- 死亡捐赠者移植 (DDKT) 的预测模型往往不适用于活体捐赠者移植 (LDKT).
- 现有的模型经常依赖于移植后的数据,这限制了LDKT早期恢复的预测.
研究的目的:
- 开发和验证一个预测模型,用于在活体捐赠者移植 (LDKT) 中早期恢复功能.
- 创建一个实用的工具,利用移植前的变量来预测移植功能.
- 通过外部验证来评估预测模型的通用性.
主要方法:
- 对来自三个机构的3335名LDKT接受者进行了回顾性队列研究.
- 一个综合模型和一个基本参数模型是使用移植前的供体和受体数据开发的.
- 使用平均绝对误差 (MAE) 和根平均平方误差 (RMSE) 评估模型性能,并进行外部验证.
主要成果:
- 两种模型都表现出高的预测准确性,综合模型实现MAE为0.15和RMSE为0.36 (内部),MAE为0.14和RMSE为0.18 (外部).
- 基本参数模型的预测准确度与综合模型的预测准确度相当.
- 基于基本参数模型开发了一个Nomogram和一个移动计算器应用程序,表明临床实用性.
结论:
- 通过使用基本的移植前变量,成功开发了一种用于预测LDKT早期功能恢复的实用模型.
- 该模型通过外部验证证明了强大的通用性,使其适合临床实施.
- 开发的Nomogram和移动应用程序为临床医生提供实时决策支持,增强临床实践.
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