Clinical characteristics and immune function analysis of COVID-19
Medical Journal of Wuhan University
; 41(4):529-532 and 546, 2020.
Article
in Chinese
| Scopus | ID: covidwho-616544
ABSTRACT
Objective:
To investigate the clinical characteristics in relation to the immune classification in patients with Coronavirus Disease 2019 (COVID-19).Methods:
We retrospectively studied the clinical data, cellular and humoral immune function tests results of 101 cases of COVID-19 confirmed by our hospital. The patients were classified according to the Chinese guideline for COVID-19 diagnosis and treatment and divided into two groups as non-severe group and severe group, and the results of cellular and humoral immune function tests were compared.Results:
The patients in the severe group were older on average, and the proportion of patients with underlying disease was higher. The counts of CD3, CD4, CD8, CD19, and CD16+CD56 T cells were significantly less in the severe group than in the non-severe group (P0.05). Levels of IgG, IgM, IgA, IgE, complement C3, and complement C4 were determined by mmunoassay, and no difference was found between the two groups. The diagnostic value of the cellular immune cells counts was analyzed by ROC curve. The area under the curve (AUC) of CD3, CD4, CD8, CD19, and CD16+CD56 T cells was 0.987 3, 0.969 3, 0.965 8, 0.817 4, and 0.658 7, respectively (P0.05), and the cut-off values for CD3, CD4, CD8, CD19, and CD16+CD56 T cells were 575.5, 390.0, 214.5, 111.0, and 127.5 cells/μL.Conclusion:
Elderly COVID-19 patients with basic diseases are more likely to develop into severe patients. The depletion of each immune cells are more obvious in severe patients. Cellular immune function is helpful to determine the condition of COVID-19 pneumonia patients. © 2020, Editorial Board of Medical Journal of Wuhan University. All right reserved.
Full text:
Available
Collection:
Databases of international organizations
Database:
Scopus
Type of study:
Prognostic study
Language:
Chinese
Journal:
Medical Journal of Wuhan University
Year:
2020
Document Type:
Article
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