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新型冠状病毒肺炎及其他肺炎的实验室指标:400天随访期间鉴别诊断及动态变化比较分析

Laboratory indicators in COVID-19 and other pneumonias: Analysis for differential diagnosis and comparison of dynamic changes during 400-day follow-up.

作者信息

Wang Jing, Zheng Yufen, Chen Yijun, Hu Xingzhong, Peng Minfei, Fang Yicheng, Shen Bo, Lu Guoguang

机构信息

Department of Clinical Laboratory, Taizhou Hospital of Zhejiang Province Affiliated to Wenzhou Medical University, 150 Ximen Road, Linhai, Taizhou, Zhejiang Province, China.

Department of Clinical Laboratory Medicine, Wenzhou Central Hospital, Dingli Clinical School of Wenzhou Medical University, Wenzhou, Zhejiang Province, China.

出版信息

Comput Struct Biotechnol J. 2021;19:2497-2507. doi: 10.1016/j.csbj.2021.04.063. Epub 2021 Apr 27.

Abstract

BACKGROUND

COVID-19 is spreading rapidly all over the world, the patients' symptoms can be easily confused with other pneumonia types. Therefore, it is valuable to seek a laboratory differential diagnostic protocol of COVID-19 and other pneumonia types on admission, and to compare the dynamic changes in laboratory indicators during follow-up.

METHODS

A total of 143 COVID-19, 143 bacterial pneumonia and 145 conventional viral pneumonia patients were included. The model group consisted of 140 COVID-19, 80 bacterial pneumonia and 60 conventional viral pneumonia patients, who were age and sex matched. We established a differential diagnostic model based on the laboratory results of the model group on admission via a nomogram, which was validated in an external validation group. We also compared the 400-day dynamic changes of the laboratory indicators among groups.

RESULTS

LASSO regression and multivariate logistic regression showed that eosinophils (Eos), total protein (TP), prealbumin (PA), potassium (K), high-density lipoprotein cholesterol (HDLC), and low-density lipoprotein cholesterol (LDLC) could differentiate COVID-19 from other pneumonia types. The C-index of the nomogram model was 0.922. Applying the nomogram to the external validation group showed an area under the curve (AUC) of 0.902. The 400-day change trends of the laboratory indexes varied among subgroups divided by sex, age, oxygenation index (OI), and pathogen.

CONCLUSION

The laboratory model was highly accurate at providing a new method to identify COVID-19 in pneumonia patients. The 400-day dynamic changes in laboratory indicators revealed that the recovery time of COVID-19 patients was not longer than that of other pneumonia types.

摘要

背景

新型冠状病毒肺炎(COVID-19)正在全球迅速传播,患者症状容易与其他类型肺炎混淆。因此,寻求COVID-19与其他类型肺炎入院时的实验室鉴别诊断方案,并比较随访期间实验室指标的动态变化具有重要价值。

方法

纳入143例COVID-19患者、143例细菌性肺炎患者和145例传统病毒性肺炎患者。模型组由140例COVID-19患者、80例细菌性肺炎患者和60例传统病毒性肺炎患者组成,这些患者在年龄和性别上相匹配。我们通过列线图根据模型组患者入院时的实验室检查结果建立了鉴别诊断模型,并在外部验证组中进行了验证。我们还比较了各组实验室指标400天的动态变化。

结果

套索回归和多因素逻辑回归显示,嗜酸性粒细胞(Eos)、总蛋白(TP)、前白蛋白(PA)、钾(K)、高密度脂蛋白胆固醇(HDLC)和低密度脂蛋白胆固醇(LDLC)可将COVID-19与其他类型肺炎区分开来。列线图模型的C指数为0.922。将列线图应用于外部验证组,曲线下面积(AUC)为0.902。按性别、年龄、氧合指数(OI)和病原体划分的亚组中,实验室指标的400天变化趋势各不相同。

结论

该实验室模型在为肺炎患者鉴别COVID-19提供新方法方面具有高度准确性。实验室指标的400天动态变化表明,COVID-19患者的恢复时间并不比其他类型肺炎患者长。

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