Inflammatory phenotyping predicts clinical outcome in COVID-19

Respiratory Research

D. C. Cellura¹  C. M. Spalluto¹  T. M. A. Wilkinson²  A. Freeman²  N. J. Brendish²  H. Burke²  S. Poole³  T. W. Clark⁴  K. J. Staples⁵  B. L. Stuart⁶  H. T. T. Phan⁷  N. Sheard⁸  S. Williams⁸  F. Borca⁹ 

[1] School of Clinical and Experimental Sciences, Faculty of Medicine, University of Southampton, Southampton General Hospital, LF13A, South Academic Block, SO16 6YD, Southampton, UK;School of Clinical and Experimental Sciences, Faculty of Medicine, University of Southampton, Southampton General Hospital, LF13A, South Academic Block, SO16 6YD, Southampton, UK;University Hospitals Southampton NHS Foundation Trust, Southampton, UK;School of Clinical and Experimental Sciences, Faculty of Medicine, University of Southampton, Southampton General Hospital, LF13A, South Academic Block, SO16 6YD, Southampton, UK;University Hospitals Southampton NHS Foundation Trust, Southampton, UK;NIHR Southampton Biomedical Research Centre, University Hospital Southampton NHS Foundation Trust, Southampton, UK;School of Clinical and Experimental Sciences, Faculty of Medicine, University of Southampton, Southampton General Hospital, LF13A, South Academic Block, SO16 6YD, Southampton, UK;University Hospitals Southampton NHS Foundation Trust, Southampton, UK;Southampton Clinical Trials Unit, University of Southampton, Southampton, UK;NIHR Post-Doctoral Fellowship Programme, Southampton, UK;School of Clinical and Experimental Sciences, Faculty of Medicine, University of Southampton, Southampton General Hospital, LF13A, South Academic Block, SO16 6YD, Southampton, UK;University Hospitals Southampton NHS Foundation Trust, Southampton, UK;Southampton Clinical Trials Unit, University of Southampton, Southampton, UK;Wessex Investigational Sciences Hub, University Of Southampton, University Hospital Southampton NHS Foundation Trust, Southampton, UK;Southampton Clinical Trials Unit, University of Southampton, Southampton, UK;Southampton Clinical Trials Unit, University of Southampton, Southampton, UK;Clinical Informatics Research Unit Faculty of Medicine, University of Southampton, Southampton, UK;University Hospitals Southampton NHS Foundation Trust, Southampton, UK;University Hospitals Southampton NHS Foundation Trust, Southampton, UK;Clinical Informatics Research Unit Faculty of Medicine, University of Southampton, Southampton, UK;

关键词: COVID-19;    SARS-CoV-2;    IL-33;    TNF-α;    Point-of-care testing;   

DOI  :  10.1186/s12931-020-01511-z

来源: Springer

【 摘 要 】

BackgroundThe 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.MethodsWe used a multiplex cytokine assay to measure serum IL-6, IL-8, TNF, IL-1β, GM-CSF, IL-10, IL-33 and IFN-γ in 100 hospitalised patients with confirmed COVID-19 at admission to University Hospital Southampton (UK). Demographic, clinical and outcome data were collected for analysis.ResultsAge > 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).ConclusionsA 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.

【 授权许可】

CC BY