使用联合建模方法评估生物标志物和COVID-19死亡率之间的关联
Matteo Di Maso1, Serena Delbue2, Maurizio Sampietro3
1Department of Clinical Sciences and Community Health, Branch of Medical Statistics, Biometry and Epidemiology "G.A. Maccacaro", Università degli Studi di Milano, 20133 Milan, Italy.
Life (Basel, Switzerland)
|March 28, 2024
概括
像中性粒细胞,C反应蛋白,葡萄糖和LDH这样的生物标志物与COVID-19死亡率有关. 监测这些标志物,并考虑患者的年龄和性别,可以帮助评估疾病的严重程度和指导治疗.
科学领域:
- 临床医学 临床医学
- 生物统计学 生物统计学
- 流行病学 流行病学
背景情况:
- COVID-19 构成了重大的全球健康威胁,死亡率受到各种因素的影响.
- 确定COVID-19死亡率的可靠预测因素对于有效的患者管理至关重要.
研究的目的:
- 评估特定生物标志物与COVID-19死亡率之间的关联.
- 评估中性粒细胞,淋巴细胞,费里丁,C反应蛋白,葡萄糖和LDH在COVID-19结果中的预测价值.
主要方法:
- 使用贝叶斯方法的联合模型 (JMs) 来分析403名COVID-19患者的数据.
- 从单变量和多变量模型中估计的危险比率 (HRs) 和95%可信度区间 (CI).
- 在分析中包括人口因素 (性别,年龄) 和生物标志物小组.
主要成果:
- 中性粒细胞,C-反应蛋白,葡萄糖和LDH在多变量分析中与COVID-19死亡率的增加显著相关.
- 在多变量模型中,淋巴细胞和费里丁与死亡率没有显著的关联.
- 男性性别和年龄较大 (≥60岁) 也与较高的死亡风险有关.
结论:
- 生物标志物,特别是中性粒细胞,CRP,葡萄糖和LDH,对于评估COVID-19严重程度和死亡风险非常有价值.
- 将生物标志物趋势与人口统计数据相结合,可以增强患者分层,并为临床护理途径提供信息.
- 这些发现强调了住院COVID-19患者常规生物标志物监测的重要性.
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