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Citation Information: JCI Insight. 2020;5(13):e139024. https://doi.org/10.1172/jci.insight.139024.
Abstract
BACKGROUND Fatal cases of COVID-19 are increasing globally. We retrospectively investigated the potential of immunologic parameters as early predictors of COVID-19.METHODS A total of 1018 patients with confirmed COVID-19 were enrolled in our 2-center retrospective study. Clinical feature, laboratory test, immunological test, radiological findings, and outcomes data were collected. Univariate and multivariable logistic regression analyses were performed to evaluate factors associated with in-hospital mortality. Receiver operator characteristic (ROC) curves and survival curves were plotted to evaluate their clinical utility.RESULTS The counts of all T lymphocyte subsets were markedly lower in nonsurvivors than in survivors, especially CD8+ T cells. Among all tested cytokines, IL-6 was elevated most significantly, with an upward trend of more than 10-fold. Using multivariate logistic regression analysis, IL-6 levels of more than 20 pg/mL and CD8+ T cell counts of less than 165 cells/μL were found to be associated with in-hospital mortality after adjusting for confounding factors. Groups with IL-6 levels of more than 20 pg/mL and CD8+ T cell counts of less than 165 cells/μL had a higher percentage of older and male patients as well as a higher proportion of patients with comorbidities, ventilation, intensive care unit admission, shock, and death. Furthermore, the receiver operating curve of the model combining IL-6 (>20 pg/mL) and CD8+ T cell counts (<165 cells/μL) displayed a more favorable discrimination than that of the CURB-65 score. The Hosmer-Lemeshow test showed a good fit of the model, with no statistical significance.CONCLUSION IL-6 (>20 pg/mL) and CD8+ T cell counts (<165 cells/μL) are 2 reliable prognostic indicators that accurately stratify patients into risk categories and predict COVID-19 mortality.Funding This work was supported by funding from the National Natural Science Foundation of China (no. 81772477 and 81201848).
Authors
Miao Luo, Jing Liu, Weiling Jiang, Shuang Yue, Huiguo Liu, Shuang Wei
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