CuPeR模型:一个动态的在线工具,用于预测脑下垂体手术后库辛氏病的持续性和复发
Guive Sharifi1,2, Elham Paraandavaji3,2, Nader Akbari Dilmaghani2,4
1Department of Neurosurgery, Loghman Hospital, Shahid Beheshti University of Medical Sciences, Tehran, Iran.
Journal of clinical & translational endocrinology
|September 8, 2025
概括
预测库希林的发生
科学领域:
- 内分泌学 在内分泌学.
- 神经外科 神经外科
- 在瘤学瘤学.
背景情况:
- 预测库辛病 (CD) 的术后结果是具有挑战性的.
- 对于术后CD的持续性和复发 (PoRP-CD) 没有普遍可靠的模型.
研究的目的:
- 介绍CuPeR模型,一个在线动态名录.
- 预测进行下垂体手术的CD患者的术后结果.
主要方法:
- 对211名CD患者 (2010-2024) 的回顾性分析.
- 多变量逻辑回归用于识别PoRP-CD预测器.
- 内部验证和开发一个在线名ogram.
主要成果:
- 关键预测因素:症状持续时间,MRI哈迪等级,瘤部位,先前的垂体手术.
- 症状持续时间和手术前增加风险;双边瘤降低风险.
- 模型AUC-ROC:0.70;准确率:83%;特异性:96%;灵敏度:33% .
结论:
- CuPeR模型为预测PoRP-CD提供了一个实用的工具.
- 通过个性化风险评估,增强了手术前决策.
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