期刊
JOURNAL OF CLINICAL IMMUNOLOGY
卷 40, 期 7, 页码 960-969出版社
SPRINGER/PLENUM PUBLISHERS
DOI: 10.1007/s10875-020-00821-7
关键词
Coronavirus disease 2019; severe acute respiratory syndrome coronavirus 2; cytokines; lymphocyte subsets; prognosis
类别
资金
- National Natural Science Foundation [81401639]
- National Mega Project on Major Infectious Disease Prevention of China [2017ZX10103005-007]
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-alpha 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.
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