Longitudinal Analysis of Electronic Health Information to Identify Possible COVID-19 Sequelae
- PMID: 36564152
- PMCID: PMC9881771
- DOI: 10.3201/eid2902.220712
Longitudinal Analysis of Electronic Health Information to Identify Possible COVID-19 Sequelae
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.
Keywords: COVID-19; SARS-CoV-2; United States; coronavirus disease; coronaviruses; electronic health information sequelae; longitudinal analysis; respiratory infections; severe acute respiratory syndrome coronavirus 2; viruses; zoonoses.
References
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- Centers for Disease Control and Prevention. Public health recommendations: evaluating and caring for patients with post-COVID conditions: interim guidance [cited 2022 Aug 22]. https://www.cdc.gov/coronavirus/2019-ncov/hcp/clinical-care/post-covid-p...
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