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. Electronic supplementary material The online version of this article (10.1007/s10875-020-00821-7) contains supplementary material, which is available to authorized users.
【저자키워드】 severe acute respiratory syndrome coronavirus 2, Coronavirus disease 2019, Cytokines, Prognosis, Lymphocyte subsets, 【초록키워드】 COVID-19, coronavirus disease, T cells, B cells, NK cell, interleukin-6, cytokine, outcome, CD4, CD8, lymphocyte, T cell, Sensitivity and specificity, Lymphocyte subset, Patient, death, receptor, group, threshold, Admission, predict, marker, Combination, Concentration, Analysis, Hospital stay, In-hospital death, tumor necrosis factor-α, supplementary material, participant, serum cytokine, Tongji Hospital, approach, decrease, Result, enrolled, was used, the disease, was performed, exhibited, provide, subjects, subset, survived, Significant, patients with COVID-19, positively correlated, with COVID-19, 【제목키워드】 SARS-CoV-2, prediction, Model,