A 9-mRNA signature measured from whole blood by a prototype PCR panel predicts 28-day mortality upon admission of critically ill COVID-19 patients
oleh: Claire Tardiveau, Claire Tardiveau, Guillaume Monneret, Guillaume Monneret, Anne-Claire Lukaszewicz, Anne-Claire Lukaszewicz, Valérie Cheynet, Valérie Cheynet, Elisabeth Cerrato, Elisabeth Cerrato, Katia Imhoff, Katia Imhoff, Estelle Peronnet, Estelle Peronnet, Maxime Bodinier, Maxime Bodinier, Louis Kreitmann, Louis Kreitmann, Sophie Blein, Sophie Blein, Jean-François Llitjos, Jean-François Llitjos, Jean-François Llitjos, Filippo Conti, Filippo Conti, Morgane Gossez, Morgane Gossez, Marielle Buisson, Hodane Yonis, Martin Cour, Laurent Argaud, Marie-Charlotte Delignette, Florent Wallet, Frederic Dailler, Céline Monard, Karen Brengel-Pesce, Karen Brengel-Pesce, Fabienne Venet, Fabienne Venet, the RICO study group
| Format: | Article |
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| Diterbitkan: | Frontiers Media S.A. 2022-11-01 |
Deskripsi
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.