在使用基线,治疗和治疗后变量进行血管内卒中治疗时评估结果预测模型
Johanna M Ospel1,2,3, Aravind Ganesh3, Manon Kappelhof4
1Department of Clinical Neurosciences University of Calgary Calgary Alberta Canada.
Stroke (Hoboken, N.J.)
|January 26, 2026
概括
通过包括治疗和治疗后变量,可以改善急性缺血性中风的内血管治疗后预测结果. 目前的模型错误地分类了许多患者,突出了在中风干预后预测功能独立性的局限性.
科学领域:
- 神经学 神经学
- 医学统计 医学统计
- 干预心脏病学 干预心脏病学
背景情况:
- 目前用于预测急性缺血性中风内血管治疗后结果的统计模型主要使用基线变量.
- 需要通过代地纳入与治疗相关的和治疗后的变量来评估这些模型的性能.
研究的目的:
- 通过代添加基线,治疗相关和治疗后变量来评估内血管治疗中风结果预测模型的性能.
- 确定不同类型的变量对结果预测准确性的贡献.
主要方法:
- 使用ESCAPE-NA1试验数据开发了四种多变量后勤回归模型.
- 模型1:基线变量;模型2:基线+治疗变量;模型3:模型2+早期治疗后变量;模型4:模型3+晚期治疗后变量.
- 使用接收器运行特征曲线 (AUC) 下的面积和Shapley值来评估可变贡献的模型性能比较.
主要成果:
- 接收器运行特征曲线 (AUC) 下的面积反复从0.74 (仅基线) 提高到0.82 (所有变量).
- 即使使用最全面的模型,19.8%的实现功能独立的患者被错误分类.
- 患者的年龄,严重的不良事件 (肺炎) 和早期的内出血是导致结果变异的重要因素.
结论:
- 除了基线变量之外的因素对急性缺血性中风的内血管治疗后的结果有显著的贡献.
- 目前的结果预测模型的准确性有限,错误分类率很高.
- 在临床实践中应用现有模型时建议谨慎,因为它们的局限性.
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