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

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 moni...

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Bibliographic Details
Main Authors: 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
Language:English
Published: Centers for Disease Control and Prevention 2023-02-01
Series:Emerging Infectious Diseases
Subjects:
COVID-19
coronavirus disease
severe acute respiratory syndrome coronavirus 2
SARS-CoV-2
coronaviruses
viruses
Online Access:https://wwwnc.cdc.gov/eid/article/29/2/22-0712_article
Description
Summary: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.
ISSN:1080-6040
1080-6059

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