Abstract
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.
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