Computable Clinical Phenotyping of Postacute Sequelae of COVID-19 in Pediatrics Using Real-World Data

Tomini A Fashina; Christine M Miller; Elijah Paintsil; Linda M Niccolai; Cynthia Brandt; Carlos R Oliveira

doi:10.1093/jpids/piac132

Computable Clinical Phenotyping of Postacute Sequelae of COVID-19 in Pediatrics Using Real-World Data

J Pediatric Infect Dis Soc. 2023 Feb 27;12(2):113-116. doi: 10.1093/jpids/piac132.

Authors

Tomini A Fashina¹, Christine M Miller², Elijah Paintsil^{2

3

4}, Linda M Niccolai⁴, Cynthia Brandt⁵, Carlos R Oliveira^{2

5}

Affiliations

¹ Yale University School of Public, New Haven, Connecticut, USA.
² Department of Pediatrics, Section of Infectious Diseases and Global Health, Yale University School of Medicine, New Haven, Connecticut, USA.
³ Department of Pharmacology, Yale University School of Medicine, New Haven, Connecticut, USA.
⁴ Department of Epidemiology of Microbial Diseases, Yale University School of Public, New Haven, Connecticut, USA.
⁵ Department of Biostatistics, Section of Health Informatics, Yale University School of Public Health, New Haven, Connecticut, USA, USA.

Abstract

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

Keywords: COVID-19; pediatrics; postacute sequelae of COVID-19 (PASC).

Publication types

Research Support, N.I.H., Extramural

MeSH terms

COVID-19*
Child
Humans
Pediatrics*

Abstract

Publication types

MeSH terms

Grants and funding