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Prediction Model Based on the Combination of Cytokines and Lymphocyte Subsets for Prognosis of SARS-CoV-2 Infection.
Journal of Clinical Immunology ( IF 9.1 ) Pub Date : 2020-07-13 , DOI: 10.1007/s10875-020-00821-7
Ying Luo 1 , Liyan Mao 1 , Xu Yuan 1 , Ying Xue 2 , Qun Lin 1 , Guoxing Tang 1 , Huijuan Song 1 , Feng Wang 1 , Ziyong Sun 1
Affiliation  

Background

There are currently rare satisfactory markers for predicting the death of patients with coronavirus disease 2019 (COVID-19). The aim of this study is to establish a model based on the combination of serum cytokines and lymphocyte subsets for predicting the prognosis of the disease.

Methods

A total of 739 participants with COVID-19 were enrolled at Tongji Hospital from February to April 2020 and classified into fatal (n = 51) and survived (n = 688) groups according to the patient’s outcome. Cytokine profile and lymphocyte subset analysis was performed simultaneously.

Results

The fatal patients exhibited a significant lower number of lymphocytes including B cells, CD4+ T cells, CD8+ T cells, and NK cells and remarkably higher concentrations of cytokines including interleukin-2 receptor, interleukin-6, interleukin-8, and tumor necrosis factor-α on admission compared with the survived subjects. A model based on the combination of interleukin-8 and the numbers of CD4+ T cells and NK cells showed a good performance in predicting the death of patients with COVID-19. When the threshold of 0.075 was used, the sensitivity and specificity of the prediction model were 90.20% and 90.26%, respectively. Meanwhile, interleukin-8 was found to have a potential value in predicting the length of hospital stay until death.

Conclusions

Significant increase of cytokines and decrease of lymphocyte subsets are found positively correlated with in-hospital death. A model based on the combination of three markers provides an attractive approach to predict the prognosis of COVID-19.



中文翻译:

基于细胞因子和淋巴细胞亚群组合的SARS-CoV-2感染预测模型。

背景

当前,很少有令人满意的标志物可以预测2019年冠状病毒病患者的死亡(COVID-19)。这项研究的目的是基于血清细胞因子和淋巴细胞亚群的组合建立模型,以预测疾病的预后。

方法

到2020年2月至2020年4月,共有739名COVID-19受试者入选同济医院, 根据患者的结局分为致命组(n  = 51)和存活组(n = 688)。同时进行细胞因子谱和淋巴细胞亚群分析。

结果

致命患​​者的淋巴细胞数量显着减少,包括B细胞,CD4 + T细胞,CD8 + T细胞和NK细胞,并且细胞因子浓度高得多,包括白介素2受体,白介素6,白介素8和肿瘤坏死。入院时的α因子与存活的受试者相比。基于白介素8和CD4 + T细胞和NK细胞数量的组合的模型在预测COVID-19患者的死亡方面表现出良好的表现。当使用阈值0.075时,预测模型的敏感性和特异性分别为90.20%和90.26%。同时,发现白介素8在预测死亡之前的住院时间方面具有潜在价值。

结论

发现细胞因子的显着增加和淋巴细胞亚群的减少与医院内死亡呈正相关。基于三种标记物组合的模型提供了一种有吸引力的方法来预测COVID-19的预后。

更新日期:2020-07-13
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