Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
. 2020 Dec:101:342-345.
doi: 10.1016/j.ijid.2020.10.003. Epub 2020 Oct 9.

A score combining early detection of cytokines accurately predicts COVID-19 severity and intensive care unit transfer

Affiliations

A score combining early detection of cytokines accurately predicts COVID-19 severity and intensive care unit transfer

Carole Nagant et al. Int J Infect Dis. 2020 Dec.

Abstract

Objectives: We aimed to explore cytokine profile in patients as it relates to Coronavirus Disease 2019 (COVID-19) severity, and to establish a predictive cytokine score to discriminate severe from non-severe cases and provide a prognosis parameter for patients that will require intensive care unit (ICU) transfer.

Methods: Serum samples of 63 patients diagnosed with SARS-CoV-2 infection were collected early after hospital admission (day 0-3). Patients were categorized in five groups based on the clinical presentation, the PaO2/FiO2 ratio and the requirement of mechanical ventilation.

Results: Three cytokines, IL-6, IL-8 and IL-10, were markedly higher in severe forms (n = 44) than in non-severe forms (n = 19) (p < 0.005). A score combining levels of these three cytokines (IL-6*IL-8*IL-10) had the highest performance to predict severity: sensitivity of 86.4% (95% CI, 72.4-94.8) and specificity of 94.7% (95% CI, 74.0-99.9) for a cutoff value of 2068 pg/mL. Elevated levels of IL-6, IL-8 and IL-10 were also found in critically ill patients. The combination of IL-6*IL-10 serum levels allowed the highest predictability for ICU transfer: AUC of 0.898 (p < 0.0001).

Conclusion: The combinatorial IL-6*IL-8*IL-10 score at presentation was highly predictive of the progression to a severe form of the disease, and could contribute to improve patient triage and to adapt therapeutic strategy within clinical trials more accurately and efficiently.

Keywords: COVID-19; Disease severity; IL-6; Inflammatory cytokines; Intensive care unit; Prediction.

PubMed Disclaimer

Figures

Figure 1
Figure 1
Predictive power of early cytokine measurement. ROC curves of cytokines, CRP and fibrinogen levels to diagnose (A) non-severe versus severe and (B) critical versus non-critical patients with COVID-19. Kaplan-Meier analyses of ICU transfer in patients with (C) low (n = 50) versus high IL-6 levels (n = 13), (D) low (n = 46) versus high IL-10 levels (n = 17) and (E) low (n = 44) versus high IL-6*IL-10 score (n = 19).

References

    1. Chen G., Wu D., Guo W., Cao Y., Huang D., Wang H. Clinical and immunological features of severe and moderate Coronavirus Disease 2019. J Clin Invest. 2020;130(5):2620–2629. doi: 10.1172/JCI137244. - DOI - PMC - PubMed
    1. Chen X., Zhao B., Qu Y., Chen Y., Xiong J., Feng Y. Detectable serum SARS-CoV-2 viral load (RNAaemia) is closely associated with drastically elevated interleukin 6 (IL-6) level in critically ill COVID-19 patients. Clin Infect Dis. 2020 doi: 10.1093/cid/ciaa449. - DOI - PMC - PubMed
    1. Lucas C., Wong P., Klein H., Castro T.B.R., Silva J., Sundaram M. Longitudinal analyses reveal immunological misfiring in severe COVID-19. Nature. 2020 doi: 10.1038/s41586-020-2588-y. - DOI - PMC - PubMed
    1. Vabret N., Britton G.J., Gruber C., Hegde S., Kim J., Kuksin M. Immunology of COVID-19: current state of the science. Immunity. 2020;52(6):910–941. doi: 10.1016/j.immuni.2020.05.002. - DOI - PMC - PubMed
    1. Wan S., Yi Q., Fan S., Lv J., Zhang X., Guo L. Relationships among lymphocyte subsets, cytokines, and the pulmonary inflammation index in coronavirus (COVID-19) infected patients. Br J Haematol. 2020;189(3):428–437. doi: 10.1111/bjh.16659. - DOI - PMC - PubMed

MeSH terms