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Longitudinal Analysis of Electronic Health Information to Identify Possible COVID-19 Sequelae.
Emerg Infect Dis ; 29(2): 389-392, 2023 Feb.
Article en En | MEDLINE | ID: mdl-36564152
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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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Coronavirus del Síndrome Respiratorio de Oriente Medio / COVID-19 Tipo de estudio: Risk_factors_studies Límite: Humans Idioma: En Revista: Emerg Infect Dis Asunto de la revista: DOENCAS TRANSMISSIVEIS Año: 2023 Tipo del documento: Article

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Coronavirus del Síndrome Respiratorio de Oriente Medio / COVID-19 Tipo de estudio: Risk_factors_studies Límite: Humans Idioma: En Revista: Emerg Infect Dis Asunto de la revista: DOENCAS TRANSMISSIVEIS Año: 2023 Tipo del documento: Article
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