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为严重和致命的COVID-19开发和验证名录模型

Jiahao Chen¹, Qingfeng Hu², Ruifang Zhong¹

¹Department of Clinical Laboratory, Shengli Clinical Medical College of Fujian Medical University, Fuzhou, Fujian, China.

Scientific reports

|November 25, 2024

概括

这项研究开发了名图模型,以预测严重和致命的COVID-19结果. 关键预测因素包括严重病例的年龄,中性粒细胞,乳酸脱酶,淋巴细胞和白蛋白水平,以及致命病例的病史.

科学领域:

传染性疾病传染性疾病
临床医学临床医学
生物统计学生物统计学

背景情况:

COVID-19呈现出不断升级的传染性和免疫抵抗性,导致严重病例和死亡率增加.
有效的风险分层对于及时的临床干预和改善患者结果至关重要.
现有的预测工具需要改进,以准确识别高风险的COVID-19患者.

研究的目的:

开发和验证住院COVID-19患者的严重和致命结局的诺姆图预测模型.
通过识别高风险患者来增强临床管理策略.
通过早期风险评估来降低COVID-19相关的发病率和死亡率.

主要方法:

对1600名COVID-19患者的回顾性分析,分为轻度,严重和致命的组.
在临床和实验室数据上使用单变量和多个阶段回归分析开发预测模型.
使用接收器运行特征 (ROC) 曲线,霍斯默-莱梅斯测试和决策曲线分析验证名ogram模型.

主要成果:

纳米图包括年龄,中性粒细胞 (NEU),乳酸脱酶 (LDH),淋巴细胞 (LYM) 和白蛋白 (ALB) 预测了严重的COVID-19 (AUC=0.771).
针对致命结局的单独名图识别了脑梗塞/癌症史,LDH和ALB作为关键因素 (AUC=0.748).
这两种模型都表现出良好的歧视和校准,用于预测严重和致命的COVID-19病例.

结论:

高龄,NEU,LDH和LYM,ALB的降低是严重COVID-19的危险因素.
脑梗塞/癌症史,LDH升高和ALB降低预测危急病患者的致命结果.
诺米图模型为早期风险预测提供了有价值的工具,有助于及时干预,以减少COVID-19的严重程度和死亡率.

关键词:

在 COVID-19 疫情中,发展发展发展发展发展诺莫格拉姆模型的模型风险因素风险因素验证验证验证验证

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