与临床编码长期COVID相关的患者特征:使用电子健康记录的OpenSAFELY研究
Yinghui Wei1,2, Elsie Mf Horne2,3, Rochelle Knight2,3,4,5
1Centre for Mathematical Sciences, School of Engineering, Computing and Mathematics, University of Plymouth, Plymouth, United Kingdom yinghui.wei@plymouth.ac.uk.
电子健康记录中的长COVID编码是不完整的. 关键的患者因素,如女性性别,年龄较小,肥胖和某些健康状况与编码长期COVID有关,但结果需要谨慎解释.
科学领域:
- 公共卫生 公共卫生
- 流行病学 流行病学
- 医疗信息学 医疗信息学
背景情况:
- 电子健康记录 (EHR) 显示了长期COVID的不完整的临床编码.
- 尽管有越来越多的报道,但准确的长期COVID病例识别仍然是一个挑战.
研究的目的:
- 为了确定与临床编码长期COVID相关的患者特征.
- 分析与长期COVID诊断有关的人口,行为和临床因素.
主要方法:
- 使用英格兰OpenSAFELY-TPP电子健康记录 (2020-2022) 进行的一项大型队列研究.
- 分析包括人口统计,健康行为和临床因素.
- 编码长期COVID的估计危险比率,比较疫苗接种前后的时间.
主要成果:
- 在1790万成年人中,0.21%的成年人编码了长期COVID.
- 相关因素包括女性性别,年龄较小,肥胖,贫困程度较低,吸烟,频繁的咨询,喘,心理健康状况,病毒后疲劳和牛皮.
- 接种疫苗后的关联减弱;在住院COVID-19病例中发生率更高.
结论:
- 与编码长期COVID相关的患者特征存在显著差异.
- 在EHR中长期COVID的记录不足,需要谨慎地解释研究结果.
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