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Inflammatory phenotyping predicts clinical outcome in COVID-19

Inflammatory phenotyping predicts clinical outcome in COVID-19
Inflammatory phenotyping predicts clinical outcome in COVID-19

Background: The COVID-19 pandemic has led to more than 760,000 deaths worldwide (correct as of 16th August 2020). Studies suggest a hyperinflammatory response is a major cause of disease severity and death. Identitfying COVID-19 patients with hyperinflammation may identify subgroups who could benefit from targeted immunomodulatory treatments. Analysis of cytokine levels at the point of diagnosis of SARS-CoV-2 infection can identify patients at risk of deterioration. Methods: We used a multiplex cytokine assay to measure serum IL-6, IL-8, TNF, IL-1β, GM-CSF, IL-10, IL-33 and IFN-γin 100 hospitalised patients with confirmed COVID-19 at admission to University Hospital Southampton (UK). Demographic, clinical and outcome data were collected for analysis. Results: Age > 70 years was the strongest predictor of death (OR 28, 95% CI 5.94, 139.45). IL-6, IL-8, TNF, IL-1β and IL-33 were significantly associated with adverse outcome. Clinical parameters were predictive of poor outcome (AUROC 0.71), addition of a combined cytokine panel significantly improved the predictability (AUROC 0.85). In those ≤70 years, IL-33 and TNF were predictive of poor outcome (AUROC 0.83 and 0.84), addition of a combined cytokine panel demonstrated greater predictability of poor outcome than clinical parameters alone (AUROC 0.92 vs 0.77). Conclusions: A combined cytokine panel improves the accuracy of the predictive value for adverse outcome beyond standard clinical data alone. Identification of specific cytokines may help to stratify patients towards trials of specific immunomodulatory treatments to improve outcomes in COVID-19.

COVID-19, IL-33, Point-of-care testing, SARS-CoV-2, TNF-α
1465-9921
Burke, Hannah
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Freeman, Anna
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Cellura, Doriana
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Stuart, Beth L.
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Brendish, Nathan J.
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Poole, Stephen
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Borca, Florina
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Phan, Hang T.T.
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Sheard, Natasha
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Williams, Sarah
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Spalluto, C. Mirella
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Staples, Karl J.
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Clark, Tristan W.
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Wilkinson, Tom M.A.
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REACT COVID Investigators
Burke, Hannah
a9bb9391-4704-4584-aeb7-e69fe0acbdb8
Freeman, Anna
3d83f907-e7ce-4649-a018-a7a31b19f934
Cellura, Doriana
e4cffc4c-0e12-40e7-ad13-e90e3fb55332
Stuart, Beth L.
626862fc-892b-4f6d-9cbb-7a8d7172b209
Brendish, Nathan J.
a8a4189e-01eb-4ab3-933e-a24cd188a4d7
Poole, Stephen
440d7904-ab72-469c-892b-c910cd1cb19b
Borca, Florina
31fc3965-6bcf-4fd6-85bc-8b0f99f62473
Phan, Hang T.T.
2811b94c-62b7-459d-9cc1-c88057008e3b
Sheard, Natasha
03c5f465-4f23-4dbd-a1b3-46a95acb5ac8
Williams, Sarah
f98f47db-b1d6-42c2-b0eb-7c0cb9a981d0
Spalluto, C. Mirella
6802ad50-bc38-404f-9a19-40916425183b
Staples, Karl J.
e0e9d80f-0aed-435f-bd75-0c8818491fee
Clark, Tristan W.
712ec18e-613c-45df-a013-c8a22834e14f
Wilkinson, Tom M.A.
8c55ebbb-e547-445c-95a1-c8bed02dd652

Burke, Hannah, Freeman, Anna, Cellura, Doriana, Stuart, Beth L., Brendish, Nathan J., Poole, Stephen, Borca, Florina, Phan, Hang T.T., Sheard, Natasha, Williams, Sarah, Spalluto, C. Mirella, Staples, Karl J., Clark, Tristan W. and Wilkinson, Tom M.A. , REACT COVID Investigators (2020) Inflammatory phenotyping predicts clinical outcome in COVID-19. Respiratory Research, 21 (1), [245]. (doi:10.1186/s12931-020-01511-z).

Record type: Article

Abstract

Background: The COVID-19 pandemic has led to more than 760,000 deaths worldwide (correct as of 16th August 2020). Studies suggest a hyperinflammatory response is a major cause of disease severity and death. Identitfying COVID-19 patients with hyperinflammation may identify subgroups who could benefit from targeted immunomodulatory treatments. Analysis of cytokine levels at the point of diagnosis of SARS-CoV-2 infection can identify patients at risk of deterioration. Methods: We used a multiplex cytokine assay to measure serum IL-6, IL-8, TNF, IL-1β, GM-CSF, IL-10, IL-33 and IFN-γin 100 hospitalised patients with confirmed COVID-19 at admission to University Hospital Southampton (UK). Demographic, clinical and outcome data were collected for analysis. Results: Age > 70 years was the strongest predictor of death (OR 28, 95% CI 5.94, 139.45). IL-6, IL-8, TNF, IL-1β and IL-33 were significantly associated with adverse outcome. Clinical parameters were predictive of poor outcome (AUROC 0.71), addition of a combined cytokine panel significantly improved the predictability (AUROC 0.85). In those ≤70 years, IL-33 and TNF were predictive of poor outcome (AUROC 0.83 and 0.84), addition of a combined cytokine panel demonstrated greater predictability of poor outcome than clinical parameters alone (AUROC 0.92 vs 0.77). Conclusions: A combined cytokine panel improves the accuracy of the predictive value for adverse outcome beyond standard clinical data alone. Identification of specific cytokines may help to stratify patients towards trials of specific immunomodulatory treatments to improve outcomes in COVID-19.

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Accepted/In Press date: 14 September 2020
Published date: 22 September 2020
Keywords: COVID-19, IL-33, Point-of-care testing, SARS-CoV-2, TNF-α

Identifiers

Local EPrints ID: 443925
URI: http://eprints.soton.ac.uk/id/eprint/443925
ISSN: 1465-9921
PURE UUID: c8634eab-2ff9-44fb-a676-0b02fc8852bf
ORCID for Beth L. Stuart: ORCID iD orcid.org/0000-0001-5432-7437
ORCID for Nathan J. Brendish: ORCID iD orcid.org/0000-0002-9589-4937
ORCID for Karl J. Staples: ORCID iD orcid.org/0000-0003-3844-6457
ORCID for Tristan W. Clark: ORCID iD orcid.org/0000-0001-6026-5295

Catalogue record

Date deposited: 16 Sep 2020 16:40
Last modified: 07 Oct 2021 04:03

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Contributors

Author: Hannah Burke
Author: Anna Freeman
Author: Doriana Cellura
Author: Beth L. Stuart ORCID iD
Author: Stephen Poole
Author: Florina Borca
Author: Hang T.T. Phan
Author: Natasha Sheard
Author: Sarah Williams
Author: C. Mirella Spalluto
Author: Karl J. Staples ORCID iD
Corporate Author: REACT COVID Investigators

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