在重症监护试验中计划预测丰富的真实世界因果证据:范围审查
Benjamin Skov Kaas-Hansen1,2, Anders Granholm1, Praleene Sivapalan1
1Department of Intensive Care, Copenhagen University Hospital, Rigshospitalet, Copenhagen, Denmark.
Acta anaesthesiologica Scandinavica
|August 31, 2023
概括
在重症监护中的随机临床试验往往缺乏确的结果. 这次审查发现没有使用真实世界数据进行预测丰富的试验,突出了改善试验设计和结果的错失机会.
科学领域:
- 关键护理医学 关键护理医学
- 临床试验方法论 临床试验方法论
- 流行病学 流行病学
背景情况:
- 在重症监护中的随机临床试验 (RCT) 面临着诸如乐观效果大小假设和未能考虑异质治疗效应等挑战.
- 现实世界的因果证据可以为预测丰富策略提供信息,以增强RCT,但其应用尚未得到充分记录.
研究的目的:
- 进行临床临床临床试验在重症监护的范围审查.
- 评估二次数据源的因果证据在这些试验中被用于计划的预测丰富的程度.
主要方法:
- 对从2018年1月1日起出版的,招募成年重病患者的RCT的10个一般和专业期刊进行系统搜索.
- 收集了22个变量的元数据,包括干预类型,招聘持续时间和早期停止原因.
- 具体研究了从二次数据中获得的因果证据用于计划预测丰富的使用.
主要成果:
- 包括316个独特的RCT,涉及268,563名参与者,其中大多数测试药物干预 (55%) 或管理策略 (32%).
- 大多数试验 (83%) 随机选择的参与者不到1000人,平均入学时间为2.2年.
- 关键的是,没有一项经过审查的RCT利用从二次数据中获得的因果关系证据来计划预测丰富.
结论:
- 需要将现实世界的重症监护数据整合到RCT中,以改善试验设计和克服局限性.
- 从干预/分析流行病学和数据科学中利用方法对于有效利用重症监护数据至关重要.
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