Longitudinal Analysis of Electronic Health Information to Identify Possible COVID-19 Sequelae
oleh: Eleanor S. Click, Donald Malec, Jennifer R. Chevinsky, Guoyu Tao, Michael Melgar, Jennifer E. Giovanni, Adi V. Gundlapalli, S. Deblina Datta, Karen K. Wong
| Format: | Article |
|---|---|
| Diterbitkan: | Centers for Disease Control and Prevention 2023-02-01 |
Deskripsi
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.