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Severity of COVID-19 and adverse long-term outcomes: a retrospective cohort study based on a US electronic health record database
OBJECTIVE: To identify potential risk factors for adverse long-term outcomes (LTOs) associated with COVID-19, using a large electronic health record (EHR) database. DESIGN: Retrospective cohort study. Patients with COVID-19 were assigned into subcohorts according to most intensive treatment setting...
Autores principales: | , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BMJ Publishing Group
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9065767/ https://www.ncbi.nlm.nih.gov/pubmed/34893488 http://dx.doi.org/10.1136/bmjopen-2021-056284 |
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author | Jovanoski, Nick Chen, Xin Becker, Ursula Zalocusky, Kelly Chawla, Devika Tsai, Larry Borm, Michelle Neighbors, Margaret Yau, Vincent |
author_facet | Jovanoski, Nick Chen, Xin Becker, Ursula Zalocusky, Kelly Chawla, Devika Tsai, Larry Borm, Michelle Neighbors, Margaret Yau, Vincent |
author_sort | Jovanoski, Nick |
collection | PubMed |
description | OBJECTIVE: To identify potential risk factors for adverse long-term outcomes (LTOs) associated with COVID-19, using a large electronic health record (EHR) database. DESIGN: Retrospective cohort study. Patients with COVID-19 were assigned into subcohorts according to most intensive treatment setting experienced. Newly diagnosed conditions were classified as respiratory, cardiovascular or mental health LTOs at >30–≤90 or >90–≤180 days after COVID-19 diagnosis or hospital discharge. Multivariate regression analysis was performed to identify any association of treatment setting (as a proxy for disease severity) with LTO incidence. SETTING: Optum deidentified COVID-19 EHR dataset drawn from hospitals and clinics across the USA. PARTICIPANTS: Individuals diagnosed with COVID-19 (N=57 748) from 20 February to 4 July 2020. MAIN OUTCOMES: Incidence of new clinical conditions after COVID-19 diagnosis or hospital discharge and the association of treatment setting (as a proxy for disease severity) with their risk of occurrence. RESULTS: Patients were assigned into one of six subcohorts: outpatient (n=22 788), emergency room (ER) with same-day COVID-19 diagnosis (n=11 633), ER with COVID-19 diagnosis≤21 days before ER visit (n=2877), hospitalisation without intensive care unit (ICU; n=16 653), ICU without ventilation (n=1837) and ICU with ventilation (n=1960). Respiratory LTOs were more common than cardiovascular or mental health LTOs across subcohorts and LTO incidence was higher in hospitalised versus non-hospitalised subcohorts. Patients with the most severe disease were at increased risk of respiratory (risk ratio (RR) 1.86, 95% CI 1.56 to 2.21), cardiovascular (RR 2.65, 95% CI 1.49 to 4.43) and mental health outcomes (RR 1.52, 95% CI 1.20 to 1.91) up to 6 months after hospital discharge compared with outpatients. CONCLUSIONS: Patients with severe COVID-19 had increased risk of new clinical conditions up to 6 months after hospital discharge. The extent that treatment setting (eg, ICU) contributed to these conditions is unknown, but strategies to prevent COVID-19 progression may nonetheless minimise their occurrence. |
format | Online Article Text |
id | pubmed-9065767 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | BMJ Publishing Group |
record_format | MEDLINE/PubMed |
spelling | pubmed-90657672022-05-06 Severity of COVID-19 and adverse long-term outcomes: a retrospective cohort study based on a US electronic health record database Jovanoski, Nick Chen, Xin Becker, Ursula Zalocusky, Kelly Chawla, Devika Tsai, Larry Borm, Michelle Neighbors, Margaret Yau, Vincent BMJ Open Respiratory Medicine OBJECTIVE: To identify potential risk factors for adverse long-term outcomes (LTOs) associated with COVID-19, using a large electronic health record (EHR) database. DESIGN: Retrospective cohort study. Patients with COVID-19 were assigned into subcohorts according to most intensive treatment setting experienced. Newly diagnosed conditions were classified as respiratory, cardiovascular or mental health LTOs at >30–≤90 or >90–≤180 days after COVID-19 diagnosis or hospital discharge. Multivariate regression analysis was performed to identify any association of treatment setting (as a proxy for disease severity) with LTO incidence. SETTING: Optum deidentified COVID-19 EHR dataset drawn from hospitals and clinics across the USA. PARTICIPANTS: Individuals diagnosed with COVID-19 (N=57 748) from 20 February to 4 July 2020. MAIN OUTCOMES: Incidence of new clinical conditions after COVID-19 diagnosis or hospital discharge and the association of treatment setting (as a proxy for disease severity) with their risk of occurrence. RESULTS: Patients were assigned into one of six subcohorts: outpatient (n=22 788), emergency room (ER) with same-day COVID-19 diagnosis (n=11 633), ER with COVID-19 diagnosis≤21 days before ER visit (n=2877), hospitalisation without intensive care unit (ICU; n=16 653), ICU without ventilation (n=1837) and ICU with ventilation (n=1960). Respiratory LTOs were more common than cardiovascular or mental health LTOs across subcohorts and LTO incidence was higher in hospitalised versus non-hospitalised subcohorts. Patients with the most severe disease were at increased risk of respiratory (risk ratio (RR) 1.86, 95% CI 1.56 to 2.21), cardiovascular (RR 2.65, 95% CI 1.49 to 4.43) and mental health outcomes (RR 1.52, 95% CI 1.20 to 1.91) up to 6 months after hospital discharge compared with outpatients. CONCLUSIONS: Patients with severe COVID-19 had increased risk of new clinical conditions up to 6 months after hospital discharge. The extent that treatment setting (eg, ICU) contributed to these conditions is unknown, but strategies to prevent COVID-19 progression may nonetheless minimise their occurrence. BMJ Publishing Group 2021-12-09 /pmc/articles/PMC9065767/ /pubmed/34893488 http://dx.doi.org/10.1136/bmjopen-2021-056284 Text en © Author(s) (or their employer(s)) 2021. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ. https://creativecommons.org/licenses/by-nc/4.0/This is an open access article distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited, appropriate credit is given, any changes made indicated, and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/ (https://creativecommons.org/licenses/by-nc/4.0/) . |
spellingShingle | Respiratory Medicine Jovanoski, Nick Chen, Xin Becker, Ursula Zalocusky, Kelly Chawla, Devika Tsai, Larry Borm, Michelle Neighbors, Margaret Yau, Vincent Severity of COVID-19 and adverse long-term outcomes: a retrospective cohort study based on a US electronic health record database |
title | Severity of COVID-19 and adverse long-term outcomes: a retrospective cohort study based on a US electronic health record database |
title_full | Severity of COVID-19 and adverse long-term outcomes: a retrospective cohort study based on a US electronic health record database |
title_fullStr | Severity of COVID-19 and adverse long-term outcomes: a retrospective cohort study based on a US electronic health record database |
title_full_unstemmed | Severity of COVID-19 and adverse long-term outcomes: a retrospective cohort study based on a US electronic health record database |
title_short | Severity of COVID-19 and adverse long-term outcomes: a retrospective cohort study based on a US electronic health record database |
title_sort | severity of covid-19 and adverse long-term outcomes: a retrospective cohort study based on a us electronic health record database |
topic | Respiratory Medicine |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9065767/ https://www.ncbi.nlm.nih.gov/pubmed/34893488 http://dx.doi.org/10.1136/bmjopen-2021-056284 |
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