2022年 第8卷 第1期
《工程（英文）》 >> 2022年 第8卷 第1期 doi: 10.1016/j.eng.2020.05.014
预测新型冠状病毒肺炎患者临床预后好转概率的列线图—— 以中国浙江省为例
a State Key Laboratory for Diagnosis and Treatment of Infectious Diseases, National Clinical Research Center for Infectious Diseases, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, The First Affiliated Hospital, College of Medicine, Zhejiang University, Hangzhou 310003, China
b State Key Laboratory of Genetic Engineering, Institute of Biostatistics, School of Life Sciences, Fudan University, Shanghai 200433, China
c Division of Hepatobiliary and Pancreatic Surgery, Department of Surgery, Key Lab of Combined Multi-organ Transplantation of the Ministry of Health, The First Affiliated Hospital, College of Medicine, Zhejiang University, Hangzhou 310003, China
d Division of of Endocrinology and Metabolism, Department of Internal Medicine System, The First Affiliated Hospital, College of Medicine, Zhejiang University, Hangzhou 310003, China
# These authors contributed equally to this work.
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摘要
本研究旨在为临床医生开发一种定量方法，以预测新型冠状病毒肺炎（COVID-19）患者临床预后好转的可能性。本研究收集了2020年1月10日至2月26日入院后经实验室确诊的104例COVID-19感染患者的数据，包括患者的临床基本信息和实验室检查结果，并比较好转和未好转患者的各项参数。本研究使用最小绝对收缩和选择算法（LASSO）logistics 回归模型和双向逐步策略的多因素logistics 回归模型筛选预测预后因素，使用一致性指数（C指数）评估模型，并通过重复抽样进行内部验证，以此构建了一项新的预测列线图。截至2020年2月26日，研究中包括的104位患者（中位年龄为55岁）中，75位（72.1%）预后好转，而29位（27.9%）没有明显好转迹象。临床预后好转的患者与未好转的患者在临床特征和实验室检查结果上存在许多差异。经过多步筛选过程后，本研究筛选出5项预后因素并将其纳入列线图的构建，包括免疫球蛋白A（IgA）、C反应蛋白（CRP）、肌酸激酶（CK）、急性生理学和慢性健康评估表II（APACHE II），以及CK和APACHE II之间的相互作用。本研究建立的模型的C指数为0.962 [95%置信区间（CI）为0.931~0.993]，并且通过重复抽样验证其值仍然达到0.948。预测列线图与理想模型相比，在校准图方面显示出接近的性能，并且决策曲线和临床影响曲线显示，其在临床上具有实用性。本研究构建的列线图有助于临床医生预测每位COVID-19患者的临床预后好转的可能性，将有助于个性化的咨询和治疗。
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