Identifying endotypes of individuals after an attack of pancreatitis based on unsupervised machine learning of multiplex cytokine profiles

After an attack of pancreatitis, individuals may develop metabolic sequelae (e.g., new-onset diabetes) and/or pancreatic cancer. These new-onset morbidities are, at least in part, driven by low-grade inflammation. The aim was to study the profiles of cytokines/chemokines in individuals after an attack of pancreatitis. A commercially available panel including 31 cytokines/chemokines was investigated. Random forest classifier and unsupervised hierarchical clustering was applied to study participants (who had no persistent organ failure and did not require ICU admission) according to their cytokine/chemokine profiles.
Source: Translational Research - Category: Research Authors: Source Type: research