Three Data-Driven Phenotypes of Multiple Organ Dysfunction Syndrome Preserved from Early Childhood to Middle Adulthood

Abstract

Multiple organ dysfunction syndrome (MODS) is one of the major causes of death and long-term impairment in critically ill patients. MODS is a complex, heterogeneous syndrome consisting of different phenotypes, which has limited the development of MODS-specific therapies and prognostic models. We used an unsupervised learning approach to derive novel phenotypes of MODS based on the type and severity of six individual organ dysfunctions. In a large, multi-center cohort of pediatric, young and middle-aged adults admitted to three different intensive care units, we uncovered and characterized three distinct data-driven phenotypes of MODS which were reproducible across age groups, where independently associated with outcomes and had unique predictors of in-hospital mortality.