智能安全:用于对不良事件的证据综合的经验数据集
Shiqi Fan1,2,3, Tianqi Yu4, Xi Yang1,2,3
1MOE Key Laboratory of Population Health Across Life Cycle (Anhui Medical University), Anhui, China.
Data in brief
|October 23, 2023
概括
研究人员创建了SMART安全数据集,这是对不良事件最大的元分析集合. 这些经验数据有助于解决医疗保健证据综合中的罕见危害和偏见.
科学领域:
- 医疗保健研究的研究.
- 生物统计学 生物统计学
- 证据综合研究
背景情况:
- 综合证据对于医疗保健决策至关重要.
- 应对罕见的不良事件和有害影响的偏差存在重大挑战.
- 经验数据对于改善不良事件证据综合的方法至关重要.
研究的目的:
- 建立SMART安全数据集,这是对不良事件元分析的最大的经验数据集.
- 为方法学家和统计学家提供可靠的数据,以应对不良事件合成中的挑战.
- 提高安全结果研究的有效性和可靠性.
主要方法:
- 汇编了151个系统性审查和629个元分析,重点关注安全结果.
- 包括来自2300多个随机对照试验和362个危害结局的数据.
- 详细的数据收集有10069行和45列的试验级信息,严格检查有效性.
主要成果:
- 智能安全数据集是迄今为止关于不良事件的最大实证元分析集合.
- 该数据集包括来自众多随机对照试验的广泛安全结果数据.
- 通过双重或四次检查和对原始来源进行验证,确保了高数据有效性.
结论:
- 智能安全数据集为推进不良事件证据综合的方法提供了宝贵的资源.
- 这一数据集将有助于更好地理解和管理罕见不良事件和相关偏见.
- 建立的数据集通过可靠的安全数据支持医疗保健实践中的知情决策.
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