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

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
Source :
Emerging Infectious Diseases, Vol 29, Iss 2, Pp 389-392 (2023)
Publication Year :
2023
Publisher :
Centers for Disease Control and Prevention, 2023.

Abstract

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.

Details

Language :
English
ISSN :
10806040 and 10806059
Volume :
29
Issue :
2
Database :
Directory of Open Access Journals
Journal :
Emerging Infectious Diseases
Publication Type :
Academic Journal
Accession number :
edsdoj.623877fb0424c2f9be6414ce2ab1e44
Document Type :
article
Full Text :
https://doi.org/10.3201/eid2902.220712