比较分类入院的SARS-CoV-2患者作为COVID-19入院患者的方法,与偶发的SARS-CoV-2相比:一个队列研究
Corinne M Hohl1,2, Amber Cragg1, Elizabeth Purssell1,3
1Department of Emergency Medicine, University of British Columbia, Vancouver, British Columbia, Canada.
PloS one
|September 26, 2023
概括
在Omicron浪潮期间,大约一半的严重急性呼吸系统综合征冠状病毒2 (SARS-CoV-2) 住院病例是冠状病毒疾病2019 (COVID-19). 疾病预防控制中心的算法比马萨诸塞州的分类准确度更高,但低估了COVID-19住院病例.
科学领域:
- 传染性疾病 传染性疾病
- 公共卫生 公共卫生
- 流行病学 流行病学
背景情况:
- 区分COVID-19住院和偶然的SARS-CoV-2感染对于准确的负担评估至关重要.
- 无症状或轻微的SARS-CoV-2感染使COVID-19对医疗保健资源的影响的评估变得复杂.
研究的目的:
- 确定COVID-19住院治疗的比例,资源利用和结果.
- 为了比较CDC算法和马萨诸塞州分类在识别COVID-19入院者的有效性.
主要方法:
- 对入住不列颠哥伦比亚省医院的SARS-CoV-2阳性患者的回顾性队列研究 (2021年12月 - 2022年5月).
- 医疗记录审查,将入院者分类为主要为COVID-19或偶然的SARS-CoV-2.
- 应用CDC和马萨诸塞州分类系统来估计医院日数,ICU入院和死亡率的差异.
主要成果:
- 52%的SARS-CoV-2病例主要是因为COVID-19.
- 在COVID-19入院患者中,重症监护室治疗率 (14.0%对8.2%) 和死亡率 (12.6%对6.4%) 显著上升.
- 疾病预防控制中心的算法比马萨诸塞州的分类 (60.5%的灵敏度,78.6%的特异性) 显示出更高的灵敏度 (82.9%) 和特异性 (98.1%),但低估了COVID-19负担.
结论:
- 在Omicron浪潮期间,大约一半的SARS-CoV-2住院病例归因于COVID-19.
- 与马萨诸塞州分类相比,CDC算法是识别COVID-19入院的更准确的工具.
- 两种分类系统,特别是CDC算法,可能低估了COVID-19住院治疗的真正负担.
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