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Int J Immunopathol Pharmacol ; 35: 20587384211048567, 2021.
Article in English | MEDLINE | ID: covidwho-1463208


BACKGROUND: Coronavirus disease 2019 (COVID-19) had become a worldwide health threat. Early prediction of the severity of COVID-19 patients was important for reducing death rate and controlling this disease. METHODS AND MATERIALS: A total of 301 patients confirmed with COVID-19 in Wuhan from 8 February to 10 April 2020 were included. Clinical data were collected and analyzed. Diagnostic and prognostic utility of blood cell counts and lymphocyte subsets in COVID-19 patients were investigated. The receiver operator characteristic curve (ROC) was used in discriminating the mild and severe/critical cases. RESULTS: There were difference in blood cell counts and lymphocyte subsets among mild, severe and critical patients, which were also influenced by comorbidities and duration of disease. The area under the ROC of lymphocyte, CD3+ T cells, CD4+ T cells, and CD8+ T cells were 0.718, 0.721, 0.718, and 0.670, which were higher than that of other hematological parameters. The optimal threshold was 1205, 691, 402, and 177 per µl, respectively. Patients with higher counts of lymphocyte, CD3+ T cells, CD4+ T cells, or CD8+ T cells were correlated with shorter length of stay in hospital (p < 0.05). Multivariable Cox regression analysis showed disease severity, CD3+ T cells counts and time when the nucleic acid turned negative were independent risk factors for in-hospital death of COVID-19 patients (p < 0.05). CONCLUSION: Blood cell counts and lymphocyte subsets correlated with severity of COVID-19.

COVID-19/immunology , Lymphocyte Subsets/immunology , Adult , Aged , Aged, 80 and over , CD4 Lymphocyte Count , COVID-19/diagnosis , COVID-19/mortality , COVID-19/virology , China , Female , Hospital Mortality , Host-Pathogen Interactions , Humans , Lymphocyte Subsets/virology , Male , Middle Aged , Phenotype , Predictive Value of Tests , Prognosis , Retrospective Studies , SARS-CoV-2/immunology , SARS-CoV-2/pathogenicity , Severity of Illness Index , Time Factors , Young Adult