Immune responses affiliated with COVID-19 severity have been characterized and associated with deleterious outcomes. These approaches were mainly based on research tools not usable in routine clinical practice at the bedside. We observed that a multiplex transcriptomic panel prototype termed Immune Profiling Panel (IPP) could capture the dysregulation of immune responses of ICU COVID-19 patients at admission. Nine transcripts were associated with mortality in univariate analysis and this 9-mRNA signature remained significantly associated with mortality in a multivariate analysis that included age, SOFA and Charlson scores. Using a machine learning model with these 9 mRNA, we could predict the 28-day survival status with an Area Under the Receiver Operating Curve (AUROC) of 0.764. Interestingly, adding patients' age to the model resulted in increased performance to predict the 28-day mortality (AUROC reaching 0.839). This prototype IPP demonstrated that such a tool, upon clinical/analytical validation and clearance by regulatory agencies could be used in clinical routine settings to quickly identify patients with higher risk of death requiring thus early aggressive intensive care.
Keywords: 28-day mortality prediction; SARS-CoV-2 infection; immune response; personalized medicine; transcriptomic multiplex tool.
Copyright © 2022 Tardiveau, Monneret, Lukaszewicz, Cheynet, Cerrato, Imhoff, Peronnet, Bodinier, Kreitmann, Blein, Llitjos, Conti, Gossez, Buisson, Yonis, Cour, Argaud, Delignette, Wallet, Dailler, Monard, Brengel-Pesce, Venet and the RICO study group.