Longitudinal Analysis of Electronic Health Information to Identify Possible COVID-19 Sequelae

Ongoing symptoms might follow acute COVID-19. Using electronic health information, we compared pre‒ and post‒COVID-19 diagnostic codes to identify symptoms that had higher encounter incidence in the post‒COVID-19 period as sequelae. This method can be used for hypothesis generation and ongoing monit...

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Detalles Bibliográficos
Autores principales: Click, Eleanor S., Malec, Donald, Chevinsky, Jennifer R., Tao, Guoyu, Melgar, Michael, Giovanni, Jennifer E., Gundlapalli, Adi V., Datta, S. Deblina, Wong, Karen K.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Centers for Disease Control and Prevention 2023
Materias:
Dispatch
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9881771/
https://www.ncbi.nlm.nih.gov/pubmed/36564152
http://dx.doi.org/10.3201/eid2902.220712
Descripción
Sumario:Ongoing symptoms might follow acute COVID-19. Using electronic health information, we compared pre‒ and post‒COVID-19 diagnostic codes to identify symptoms that had higher encounter incidence in the post‒COVID-19 period as sequelae. This method can be used for hypothesis generation and ongoing monitoring of sequelae of COVID-19 and future emerging diseases.

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