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Population Attributable Fractions of Underlying Medical Conditions for Coronavirus Disease 2019 (COVID-19) Diagnosis and COVID-19 Hospitalizations, Ventilations, and Deaths Among Adults in the United States
BACKGROUND: Several underlying medical conditions have been reported to be associated with an increased risk of coronavirus disease 2019 (COVID-19) and related hospitalization and death. Population attributable fractions (PAFs) describing the proportion of disease burden attributable to underlying m...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8992235/ https://www.ncbi.nlm.nih.gov/pubmed/35531382 http://dx.doi.org/10.1093/ofid/ofac099 |
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author | Nguyen, Jennifer L Alfred, Tamuno Reimbaeva, Maya Malhotra, Deepa Khan, Farid Swerdlow, David Angulo, Frederick J |
author_facet | Nguyen, Jennifer L Alfred, Tamuno Reimbaeva, Maya Malhotra, Deepa Khan, Farid Swerdlow, David Angulo, Frederick J |
author_sort | Nguyen, Jennifer L |
collection | PubMed |
description | BACKGROUND: Several underlying medical conditions have been reported to be associated with an increased risk of coronavirus disease 2019 (COVID-19) and related hospitalization and death. Population attributable fractions (PAFs) describing the proportion of disease burden attributable to underlying medical conditions for COVID-19 diagnosis and outcomes have not been reported. METHODS: A retrospective population-based cohort study was conducted using Optum’s de-identified Clinformatics Data Mart database. Individuals were followed up from 20 January 2020 to 31 December 2020 for diagnosis and clinical progression, including hospitalization, intensive care unit admission, intubation and mechanical ventilation or extracorporeal membrane oxygenation, and death. Adjusted rate ratios and PAFs of underlying medical conditions for COVID-19 diagnosis and disease progression outcomes were estimated by age (18–49, 50–64, 65–74, or ≥75 years), sex, and race/ethnicity. RESULTS: Of 10 679 566 cohort members, 391 964 (3.7%) were diagnosed with COVID-19, of whom 87 526 (22.3%) were hospitalized. Of those hospitalized, 26 640 (30.4%) died. Overall, cardiovascular disease and diabetes had the highest PAFs for COVID-19 diagnosis and outcomes of increasing severity across age groups (up to 0.49 and 0.35, respectively). Among adults ≥75 years of age, neurologic disease had the second-highest PAFs (0.05‒0.27) after cardiovascular disease (0.26‒0.44). PAFs were generally higher in Black persons than in other race/ethnicity groups for the same conditions, particularly in the 2 younger age groups. CONCLUSIONS: A substantial fraction of the COVID-19 disease burden in the United States is attributable to cardiovascular disease and diabetes, highlighting the continued importance of COVID-19 prevention ( eg, vaccination, mask wearing, social distancing) and disease management of patients with certain underlying medical conditions. |
format | Online Article Text |
id | pubmed-8992235 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-89922352022-04-12 Population Attributable Fractions of Underlying Medical Conditions for Coronavirus Disease 2019 (COVID-19) Diagnosis and COVID-19 Hospitalizations, Ventilations, and Deaths Among Adults in the United States Nguyen, Jennifer L Alfred, Tamuno Reimbaeva, Maya Malhotra, Deepa Khan, Farid Swerdlow, David Angulo, Frederick J Open Forum Infect Dis Major Article BACKGROUND: Several underlying medical conditions have been reported to be associated with an increased risk of coronavirus disease 2019 (COVID-19) and related hospitalization and death. Population attributable fractions (PAFs) describing the proportion of disease burden attributable to underlying medical conditions for COVID-19 diagnosis and outcomes have not been reported. METHODS: A retrospective population-based cohort study was conducted using Optum’s de-identified Clinformatics Data Mart database. Individuals were followed up from 20 January 2020 to 31 December 2020 for diagnosis and clinical progression, including hospitalization, intensive care unit admission, intubation and mechanical ventilation or extracorporeal membrane oxygenation, and death. Adjusted rate ratios and PAFs of underlying medical conditions for COVID-19 diagnosis and disease progression outcomes were estimated by age (18–49, 50–64, 65–74, or ≥75 years), sex, and race/ethnicity. RESULTS: Of 10 679 566 cohort members, 391 964 (3.7%) were diagnosed with COVID-19, of whom 87 526 (22.3%) were hospitalized. Of those hospitalized, 26 640 (30.4%) died. Overall, cardiovascular disease and diabetes had the highest PAFs for COVID-19 diagnosis and outcomes of increasing severity across age groups (up to 0.49 and 0.35, respectively). Among adults ≥75 years of age, neurologic disease had the second-highest PAFs (0.05‒0.27) after cardiovascular disease (0.26‒0.44). PAFs were generally higher in Black persons than in other race/ethnicity groups for the same conditions, particularly in the 2 younger age groups. CONCLUSIONS: A substantial fraction of the COVID-19 disease burden in the United States is attributable to cardiovascular disease and diabetes, highlighting the continued importance of COVID-19 prevention ( eg, vaccination, mask wearing, social distancing) and disease management of patients with certain underlying medical conditions. Oxford University Press 2022-03-24 /pmc/articles/PMC8992235/ /pubmed/35531382 http://dx.doi.org/10.1093/ofid/ofac099 Text en © The Author(s) 2022. Published by Oxford University Press on behalf of Infectious Diseases Society of America. https://creativecommons.org/licenses/by-nc-nd/4.0/This is an Open Access article distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivs licence (https://creativecommons.org/licenses/by-nc-nd/4.0/), which permits non-commercial reproduction and distribution of the work, in any medium, provided the original work is not altered or transformed in any way, and that the work is properly cited. For commercial re-use, please contact journals.permissions@oup.com |
spellingShingle | Major Article Nguyen, Jennifer L Alfred, Tamuno Reimbaeva, Maya Malhotra, Deepa Khan, Farid Swerdlow, David Angulo, Frederick J Population Attributable Fractions of Underlying Medical Conditions for Coronavirus Disease 2019 (COVID-19) Diagnosis and COVID-19 Hospitalizations, Ventilations, and Deaths Among Adults in the United States |
title | Population Attributable Fractions of Underlying Medical Conditions for Coronavirus Disease 2019 (COVID-19) Diagnosis and COVID-19 Hospitalizations, Ventilations, and Deaths Among Adults in the United States |
title_full | Population Attributable Fractions of Underlying Medical Conditions for Coronavirus Disease 2019 (COVID-19) Diagnosis and COVID-19 Hospitalizations, Ventilations, and Deaths Among Adults in the United States |
title_fullStr | Population Attributable Fractions of Underlying Medical Conditions for Coronavirus Disease 2019 (COVID-19) Diagnosis and COVID-19 Hospitalizations, Ventilations, and Deaths Among Adults in the United States |
title_full_unstemmed | Population Attributable Fractions of Underlying Medical Conditions for Coronavirus Disease 2019 (COVID-19) Diagnosis and COVID-19 Hospitalizations, Ventilations, and Deaths Among Adults in the United States |
title_short | Population Attributable Fractions of Underlying Medical Conditions for Coronavirus Disease 2019 (COVID-19) Diagnosis and COVID-19 Hospitalizations, Ventilations, and Deaths Among Adults in the United States |
title_sort | population attributable fractions of underlying medical conditions for coronavirus disease 2019 (covid-19) diagnosis and covid-19 hospitalizations, ventilations, and deaths among adults in the united states |
topic | Major Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8992235/ https://www.ncbi.nlm.nih.gov/pubmed/35531382 http://dx.doi.org/10.1093/ofid/ofac099 |
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