COVID-19 risk stratification algorithms based on sTREM-1 and IL-6 in emergency department

Van Singer, Mathias; Brahier, Thomas; Ngai, Michelle; Wright, Julie; Weckman, Andrea M.; Erice, Clara; Meuwly, Jean-Yves; Hugli, Olivier; Kain, Kevin C.; Boillat-Blanco, Noémie

Background The COVID-19 pandemic has led to surges of patients presenting to emergency departments (ED) and potentially overwhelming health systems. Objective This study aimed to assess the predictive accuracy of host biomarkers at clinical presentation to the ED for adverse outcome. Methods Prospective observational study of PCR-confirmed COVID-19 patients in the ED of a Swiss hospital. Concentrations of inflammatory and endothelial dysfunction biomarkers were determined at clinical presentation. We evaluated the accuracy of clinical signs and these biomarkers in predicting 30-day intubation/mortality, and oxygen requirement by calculating the area under the receiver operating characteristic curve (AUROC) and by classification and regression tree analysis. Results Of 76 COVID-19 patients included, 24 were outpatients or hospitalized without oxygen requirement, 35 hospitalized with oxygen requirement and 17 intubated/died. We found that soluble triggering receptor expressed on myeloid cells (sTREM-1) had the best prognostic accuracy for 30-day intubation/mortality (AUROC 0.86; 95% CI 0.77-0.95) and interleukin-6 (IL-6) measured at presentation to the ED had the best accuracy for 30-day oxygen requirement (AUROC 0.84; 95% CI 0.74-0.94) .An algorithm based on respiratory rate and sTREM-1 predicted 30-day intubation/mortality with 94% sensitivity and 0.1 NLR. An IL-6-based algorithm had 98% sensitivity and 0.04 negative likelihood ratio (NLR) for 30-day oxygen requirement. Conclusion sTREM-1 and IL-6 concentrations in COVID-19 in the ED have good predictive accuracy for intubation/mortality and oxygen requirement. sTREM-1- and IL-6-based algorithms are highly sensitive to identify patients with adverse outcome and could serve as early triage tools.