COVID-19患者的多病态模式及其与感染严重程度的关系:MRisk-COVID研究
Marina Lleal1,2, Celia Corral-Vazquez3, Montserrat Baré4
1Institutional Committee for the Improvement of Clinical Practice Adequacy, Clinical Epidemiology and Cancer Screening Department, Parc Taulí Hospital Universitari, Institut d'Investigació i Innovació Parc Taulí (I3PT-CERCA), Universitat Autònoma de Barcelona, Sabadell, Spain.
PloS one
|August 31, 2023
概括
这项研究在COVID-19患者中确定了不同的多病症集群,揭示了与感染严重程度和死亡率增加相关的慢性疾病的特定组合,特别是在年轻人中. 了解这些模式对于预测患者的结果至关重要.
科学领域:
- 流行病学 流行病学
- 公共卫生 公共卫生
- 老年学是一门学科.
背景情况:
- 慢性疾病是已知的严重COVID-19的风险因素.
- 多病症对COVID-19结果的影响需要进一步调查.
- 这项研究解决了在COVID-19患者中探索多病症模式的需要.
研究的目的:
- 在一大群COVID-19患者中识别多病症集群.
- 评估这些群体与COVID-19感染严重程度和死亡率之间的关系.
- 根据年龄和性别分层分析.
主要方法:
- 利用了MRisk-COVID大数据研究 (14,286名患者) 的数据.
- 应用模糊c-means集群分析以确定多病态模式.
- 进行了两种类型的分析,以将群集与严重程度和死亡率相关联,按年龄和性别分层.
主要成果:
- 9.5%的患者发生严重感染,3.9%的患者死亡.
- 在多个年龄组 (21-65岁) 中确定了与严重程度/死亡率相关的多病症群.
- 特定的集群,如男性的心脏-肝脏-胃肠道和女性的糖尿病-心血管/精神衰老,在老年人群中风险更高.
结论:
- 在COVID-19患者中按性别和年龄划分的多病症集群的特征.
- 确定了与增加COVID-19严重程度和死亡率相关的特定多病态模式.
- 强调需要进一步研究预后和易受伤害的疾病概况.
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