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Leveraging Serologic Testing to Identify Children at Risk For Post-Acute Sequelae of SARS-CoV-2 Infection: An Electronic Health Record–Based Cohort Study from the RECOVER Program

Using an electronic health record–based algorithm, we identified children with Coronavirus disease 2019 (COVID-19) based exclusively on serologic testing between March 2020 and April 2022. Compared with the 131 537 polymerase chain reaction–positive children, the 2714 serology-positive children were...

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Detalles Bibliográficos
Autores principales: Mejias, Asuncion, Schuchard, Julia, Rao, Suchitra, Bennett, Tellen D., Jhaveri, Ravi, Thacker, Deepika, Bailey, L. Charles, Christakis, Dimitri A., Pajor, Nathan M., Razzaghi, Hanieh, Forrest, Christopher B., Lee, Grace M.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier Inc. 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9943558/
https://www.ncbi.nlm.nih.gov/pubmed/36822507
http://dx.doi.org/10.1016/j.jpeds.2023.02.005
Descripción
Sumario:Using an electronic health record–based algorithm, we identified children with Coronavirus disease 2019 (COVID-19) based exclusively on serologic testing between March 2020 and April 2022. Compared with the 131 537 polymerase chain reaction–positive children, the 2714 serology-positive children were more likely to be inpatients (24% vs 2%), to have a chronic condition (37% vs 24%), and to have a diagnosis of multisystem inflammatory syndrome in children (23% vs <1%). Identification of children who could have been asymptomatic or paucisymptomatic and not tested is critical to define the burden of post-acute sequelae of severe acute respiratory syndrome coronavirus 2 infection in children.