Children are small adults (when properly normalized): Transferrable/generalizable sepsis prediction.

Background: Though governed by the same underlying biology, the differential physiology of children causes the temporal evolution from health to a septic/diseased state to follow trajectories that are distinct from adult cases. As pediatric sepsis data sets are less readily available than for adult sepsis, we aim to leverage this shared underlying biology by normalizing pediatric physiological data such that it would be directly comparable to adult data, and then develop machine-learning (ML) based classifiers to predict the onset of sepsis in the pediatric population. We then externally validated the classifiers in an independent adult dataset.