对ERCP后胰腺炎临床风险预测模型的性能:系统性审查
Nasruddin Sabrie1, Gurjot Minhas2, Marcus Vaska3
1Division of Gastroenterology and Hepatology, Department of Medicine, University of Toronto, Toronto, ON, Canada.
Pancreas
|February 11, 2025
概括
在ERCP后的胰腺炎 (PEP) 正在增加. 风险预测模型显示性能可变,但可能有助于管理患者. 需要进一步的研究来评估现实世界的影响.
科学领域:
- 胃肠病学 胃肠病学
- 医疗信息学 医疗信息学
背景情况:
- 后ERCP胰腺炎 (PEP) 在内镜逆行胆血管瘤学 (ERCP) 之后是一个重大问题.
- 与PEP相关的发病率和死亡率正在上升,需要改进风险分层和缓解策略.
研究的目的:
- 系统地审查和评估ERCP后胰腺炎现有临床预测模型的性能.
- 确定最有效的模型来分层患者的风险和指导主动管理.
主要方法:
- 在主要数据库 (MEDLINE,PubMed,Cochrane,CINAHL) 进行了电子文献搜索,截至2024年4月9日.
- 评估PEP模型的细节和预测性能的研究被包括在内,如果它们报告了准确性的统计指标.
- 使用PROBAST工具评估了偏差风险.
主要成果:
- 包括19项研究,主要使用逻辑回归 (15项研究) 和机器学习模型.
- 模型性能各不相同,接收器操作曲线 (AUC) 下报告的区域在导出,内部和外部验证数据集中从0.66到0.98不等.
- 内部验证的AUC从0.66到0.97不等,外部验证的AUC从0.67到0.98.
结论:
- 对于PEP存在众多临床预测模型,表现出不同的性能水平.
- 这些工具可以通过识别那些风险较高的患者来帮助管理ERCP患者.
- 进一步的实施和前性研究至关重要,以确定这些模型在减少PEP发病率和严重程度方面的实际有效性.
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