Prognostic peripheral blood biomarkers at ICU admission predict COVID-19 clinical outcomes

ICU 入院时的预后外周血生物标志物可预测 COVID-19 临床结果

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作者:Melina Messing, Mypinder S Sekhon, Michael R Hughes, Sophie Stukas, Ryan L Hoiland, Jennifer Cooper, Nyra Ahmed, Mark S Hamer, Yicong Li, Samuel B Shin, Lin Wei Tung, Cheryl L Wellington, Don D Sin, Kevin B Leslie, Kelly M McNagny

Abstract

The COVID-19 pandemic continues to challenge the capacities of hospital ICUs which currently lack the ability to identify prospectively those patients who may require extended management. In this study of 90 ICU COVID-19 patients, we evaluated serum levels of four cytokines (IL-1β, IL-6, IL-10 and TNFα) as well as standard clinical and laboratory measurements. On 42 of these patients (binned into Initial and Replication Cohorts), we further performed CyTOF-based deep immunophenotyping of peripheral blood mononuclear cells with a panel of 38 antibodies. All measurements and patient samples were taken at time of ICU admission and retrospectively linked to patient clinical outcomes through statistical approaches. These analyses resulted in the definition of a new measure of patient clinical outcome: patients who will recover after short ICU stays (< 6 days) and those who will subsequently die or recover after long ICU stays (≥6 days). Based on these clinical outcome categories, we identified blood prognostic biomarkers that, at time of ICU admission, prospectively distinguish, with 91% sensitivity and 91% specificity (positive likelihood ratio 10.1), patients in the two clinical outcome groups. This is achieved through a tiered evaluation of serum IL-10 and targeted immunophenotyping of monocyte subsets, specifically, CD11clow classical monocytes. Both immune biomarkers were consistently elevated ( ≥15 pg/ml and ≥2.7 x107/L for serum IL-10 and CD11clow classical monocytes, respectively) in those patients who will subsequently die or recover after long ICU stays. This highly sensitive and specific prognostic test could prove useful in guiding clinical resource allocation.

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