Computable clinical phenotyping of post-acute sequelae of COVID-19 in pediatrics using real-world data


 Many questions remain unanswered concerning the long-term effects of COVID-19 in children.
 In this report, we describe a computable phenotyping algorithm for identifying children and adolescents with post-acute sequelae of COVID-19 (PASC) and pilot this tool to characterize the clinical epidemiology of pediatric PASC in a large healthcare delivery network.