风险预测模型后内镜逆行性胆固醇瘤学胰腺炎:一个系统的审查和元分析
PloS one
|September 15, 2025
概括
在ERCP后的胰腺炎 (PEP) 是一个严重的并发症. 目前的预测模型显示中度歧视,但缺乏强大的校准和外部验证,需要改进准确风险评估的方法.
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:
- 后内镜逆行性胆固醇胰腺炎 (PEP) 是ERCP的常见和严重并发症,影响患者的治疗结果和医疗费用.
- 现有的PEP多变量预测模型在预测器集,方法质量和实际适用性方面表现出相当大的变化.
研究的目的:
- 系统地审查和元分析现有的PEP多变量风险预测模型.
- 评估PEP的发病率,并确定关键预测因素和整体模型性能.
主要方法:
- 一个符合PRISMA 2020标准的系统审查和对开发或验证多变量PEP风险预测模型的研究的元分析.
- 搜索了9个数据库,截至2024年6月1日;使用PROBAST评估偏差风险,使用纽卡斯尔-太华尺度评估研究质量.
- 采用随机效应元分析,聚合PEP发病率,预测因子关联和模型性能.
主要成果:
- 分析了涉及38016名患者的24项研究 (26个模型),其聚合PEP发病率为8.48%.
- 关键预测因素包括胰腺管管道注射,胰腺注射,先前胰腺炎和导线使用. 模型性能显示了中度的歧视 (聚合OR=0.81),但校准 (38%) 和外部验证 (46%) 是有限的.
- 指出存在偏见的高风险,特别是在分析和参与者选择领域.
结论:
- 目前的PEP预测模型提供中等到高的区别,但受到校准差,外部验证不足和方法不一致的阻碍.
- 未来的研究应该集中在TRIPOD指导方针,多中心设计,连续预测器,强大的数据归算和全面验证上.
- 整合人工智能/机器学习,并将验证的工具嵌入到临床工作流中,可以提高PEP预测的准确性和实用性.
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