A Data Science Approach to Identify and Manage Multisystem Inflammatory Syndrome in Children (MIS-C) Associated with SARS-CoV-2 Infection and Kawasaki Disease in Pediatric Patients

The primary objective of this study is to design and validate a predictive decision support system for the identification, treatment and management of SARS-CoV-2 associated with multisystem inflammatory syndrome in children (MIS-C). To develop this system, we have adapted and retrained machine learning algorithms which we have previously trained in patients with Kawasaki Disease, a pediatric inflammatory vasculopathy with clinical overlap with MIS-C but different etiology. This study, performed in collaboration with the International Kawasaki Disease Registry (IKDR) consortium. This dataset contains the development and international validation data for all algorithms developed as part of this study.