使用例行收集的医疗保健数据确定心力衰竭的准确性:系统性审查和元分析
Michelle A Goonasekera1, Alison Offer1, Waseem Karsan1
1Clinical Trial Service Unit and Epidemiological Studies Unit, Oxford Population Health, University of Oxford, Oxford, UK.
常规收集的医疗保健数据 (RCD) 可以在试验中识别心力衰竭 (HF) 住院,但错过了大约三分之一的事件. 改进RCD方法需要平衡灵敏度和特异性,以尽量减少假阳性.
科学领域:
- 心血管医学 心血管医学
- 医疗信息学 医疗信息学
- 临床试验方法论 临床试验方法论
背景情况:
- 在心血管试验中确定心力衰竭 (HF) 住院费用昂贵且复杂.
- 常规收集的医疗保健数据 (RCD) 为简化HF结果确定提供了一个潜在的途径.
- 编码RCD在随机试验中用于确定HF结果的实用性需要严格评估.
研究的目的:
- 系统地审查评估基于RCD的HF结果确定与黄金标准 (GS) 方法的研究.
- 评估在临床试验中使用RCD用于确定HF结果的可行性.
主要方法:
- 对使用国际疾病分类 (ICD) 编码的RCD用于对GS方法进行HF结果确定的研究进行系统审查.
- 从MEDLINE和Embase数据库开始到2021年5月进行搜索.
- 使用双变随机效应元分析估计的总结灵敏度和特异性以及用I2统计和HSROC曲线评估的异质性.
主要成果:
- 包括58项研究,其中包括48,643个GS-adjudicated HF事件.
- RCD算法对急性HF表现出高特异性 (96.2%),但缺乏灵敏性 (63.5%).
- 对于普遍存在的HF研究,观察到类似的敏感性和特异性结果,并注意到相当大的异质性.
结论:
- RCD可以识别HF结果,但可能错过大约三分之一的事件.
- 使用RCD改进病例识别的方法也应该专注于尽量减少假阳性.
- 为了在临床试验中最佳使用,需要进一步完善RCD确定策略.
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