• David M Maslove, Tal Shapira, Kathrin Tyryshkin, Richard A Veldhoen, John C Marshall, and John Muscedere.
• Department of Critical Care Medicine, Queen's University, Kingston, ON, Canada; Department of Medicine, Queen's University, Kingston, ON, Canada; Kingston Health Sciences Center, Queen's University, Kingston, ON, Canada. Electronic address: david.maslove@queensu.ca.
• J Crit Care. 2019 Feb 1; 49: 92-98.

PurposeGene expression diagnostics have been proposed to identify critically ill patients with sepsis. Three expression-based scores have been developed, but have not been compared in a prospective validation. We sought to validate these scores using an independent dataset and analysis.MethodsWe generated gene expression profiles from 61 critically ill patients. We validated the performance of 3 expression-based sepsis scores including 1) the Sepsis MetaScore (SMS); 2) the SeptiCyte™ Lab; and 3) the FAIM3:PLAC8 ratio. Sepsis was identified as the presence of definite, probable, or possible infection in the setting of organ dysfunction (SOFA score ≥ 2).ResultsFor all 3 models, scores were significantly different between patients with and without sepsis. Discrimination was highest for the SMS (area under the receiver operating characteristics curve [AUROC 0.80 [95% CI 0.67-0.92]), with greater confidence in the presence of infection resulting in better model performance (max AUROC 0.93 [0.87-1.0]).ConclusionsAll three scores distinguished septic from non-septic ICU patients, with the SMS showing the best performance overall in our cohort. Our results suggest that models developed from the co-analysis of multiple cohorts are more generalizable. Further work is needed to identify expression-based biomarkers of response to specific therapies.Copyright © 2018 Elsevier Inc. All rights reserved.

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