Machine learning-driven identification of the gene-expression signature associated with a persistent multiple organ dysfunction trajectory in critical illness

• DOI: 10.1016/j.ebiom.2023.104938
• Publication Date: 2023-12-23T17:25:55Z
• Authors: Mihir R. Atreya; Shayantan Banerjee; Andrew J. Lautz; Matthew N. Alder; Brian M. Varisco; Hector R. Wong; Jennifer A. Muszy...; Mark W. Hall; L. Nelson Sanchez...; Rishikesan Kamale...; Natalie Z. Cvijan...; Julie C. Fitzgerald; Scott L. Weiss; Michael T. Bigham; Parag N. Jain; Adam J. Schwarz; Riad Lutfi; Jeffrey Nowak; Geoffrey L. Allen; Neal J. Thomas; Jocelyn R. Grunwell; Torrey Baines; Michael Quasney; Bereketeab Hailes...; Chris J. Lindsell
• Keywords: Organ dysfunction; Gene signature

Multiple organ dysfunction syndrome (MODS) disproportionately drives morbidity and mortality among critically ill patients. However, we lack a comprehensive understanding of its pathobiology. Identification genes associated with persistent MODS trajectory may shed light on underlying biology allow for accurate prediction those at-risk.