About: Prediction Model Based on the Combination of Cytokines and Lymphocyte Subsets for Prognosis of SARS-CoV-2 Infection

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About: Prediction Model Based on the Combination of Cytokines and Lymphocyte Subsets for Prognosis of SARS-CoV-2 Infection Goto Sponge NotDistinct Permalink

An Entity of Type : schema:ScholarlyArticle, within Data Space : covidontheweb.inria.fr associated with source document(s)

Attributes	Values
type	Academic Article research paper schema:ScholarlyArticle
isDefinedBy	Covid-on-the-Web dataset
has title	Prediction Model Based on the Combination of Cytokines and Lymphocyte Subsets for Prognosis of SARS-CoV-2 Infection
Creator	Sun, Ziyong Yuan, Xu Wang, Feng Xue, Ying Luo, Ying Song, Huijuan Lin, Qun Mao, Liyan Tang, Guoxing
Source	Medline; PMC
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. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1007/s10875-020-00821-7) contains supplementary material, which is available to authorized users.
has issue date	2020-07-13(xsd:dateTime)
bibo:doi	10.1007/s10875-020-00821-7
bibo:pmid	32661797
has license	cc-by
sha1sum (hex)	698cdf7e8708a1c2c7f55b8b887de100d7c8f498
schema:url	https://doi.org/10.1007/s10875-020-00821-7
resource representing a document's title	Prediction Model Based on the Combination of Cytokines and Lymphocyte Subsets for Prognosis of SARS-CoV-2 Infection
has PubMed Central identifier	PMC7357264
has PubMed identifier	32661797
schema:publication	J Clin Immunol
resource representing a document's body	covid:698cdf7e8708a1c2c7f55b8b887de100d7c8f498#body_text
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