Prediction Model Based on the Combination of Cytokines and Lymphocyte Subsets for Prognosis of SARS-CoV-2 Infection.
J Clin Immunol
; 40(7): 960-969, 2020 10.
Article
em En
| MEDLINE
| ID: mdl-32661797
ABSTRACT
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.Palavras-chave
Texto completo:
1
Base de dados:
MEDLINE
Assunto principal:
Pneumonia Viral
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Citocinas
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Subpopulações de Linfócitos
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Infecções por Coronavirus
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Betacoronavirus
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Modelos Biológicos
Tipo de estudo:
Diagnostic_studies
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Etiology_studies
/
Observational_studies
/
Prognostic_studies
/
Risk_factors_studies
Limite:
Aged
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Aged80
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Female
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Humans
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Male
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Middle aged
País como assunto:
Asia
Idioma:
En
Ano de publicação:
2020
Tipo de documento:
Article