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Comparing methods to classify admitted patients with SARS-CoV-2 as admitted for COVID-19 versus with incidental SARS-CoV-2: A cohort study

INTRODUCTION: Not all patients with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection develop symptomatic coronavirus disease 2019 (COVID-19), making it challenging to assess the burden of COVID-19-related hospitalizations and mortality. We aimed to determine the proportion, res...

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Autores principales: Hohl, Corinne M., Cragg, Amber, Purssel, Elizabeth, McAlister, Finlay A., Ting, Daniel K., Scheuermeyer, Frank, Stachura, Maja, Grant, Lars, Taylor, John, Kanu, Josephine, Hau, Jeffrey P., Cheng, Ivy, Atzema, Clare L., Bola, Rajan, Morrison, Laurie J., Landes, Megan, Perry, Jeffrey J., Rosychuk, Rhonda J.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10522023/
https://www.ncbi.nlm.nih.gov/pubmed/37751455
http://dx.doi.org/10.1371/journal.pone.0291580
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author Hohl, Corinne M.
Cragg, Amber
Purssel, Elizabeth
McAlister, Finlay A.
Ting, Daniel K.
Scheuermeyer, Frank
Stachura, Maja
Grant, Lars
Taylor, John
Kanu, Josephine
Hau, Jeffrey P.
Cheng, Ivy
Atzema, Clare L.
Bola, Rajan
Morrison, Laurie J.
Landes, Megan
Perry, Jeffrey J.
Rosychuk, Rhonda J.
author_facet Hohl, Corinne M.
Cragg, Amber
Purssel, Elizabeth
McAlister, Finlay A.
Ting, Daniel K.
Scheuermeyer, Frank
Stachura, Maja
Grant, Lars
Taylor, John
Kanu, Josephine
Hau, Jeffrey P.
Cheng, Ivy
Atzema, Clare L.
Bola, Rajan
Morrison, Laurie J.
Landes, Megan
Perry, Jeffrey J.
Rosychuk, Rhonda J.
author_sort Hohl, Corinne M.
collection PubMed
description INTRODUCTION: Not all patients with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection develop symptomatic coronavirus disease 2019 (COVID-19), making it challenging to assess the burden of COVID-19-related hospitalizations and mortality. We aimed to determine the proportion, resource utilization, and outcomes of SARS-CoV-2 positive patients admitted for COVID-19, and assess the impact of using the Center for Disease Control’s (CDC) discharge diagnosis-based algorithm and the Massachusetts state department’s drug administration-based classification system on identifying admissions for COVID-19. METHODS: In this retrospective cohort study, we enrolled consecutive SARS-CoV-2 positive patients admitted to one of five hospitals in British Columbia between December 19, 2021 and May 31,2022. We completed medical record reviews, and classified hospitalizations as being primarily for COVID-19 or with incidental SARS-CoV-2 infection. We applied the CDC algorithm and the Massachusetts classification to estimate the difference in hospital days, intensive care unit (ICU) days and in-hospital mortality and calculated sensitivity and specificity. RESULTS: Of 42,505 Emergency Department patients, 1,651 were admitted and tested positive for SARS-CoV-2, with 858 (52.0%, 95% CI 49.6–54.4) admitted for COVID-19. Patients hospitalized for COVID-19 required ICU admission (14.0% versus 8.2%, p<0.001) and died (12.6% versus 6.4%, p<0.001) more frequently compared with patients with incidental SARS-CoV-2. Compared to case classification by clinicians, the CDC algorithm had a sensitivity of 82.9% (711/858, 95% CI 80.3%, 85.4%) and specificity of 98.1% (778/793, 95% CI 97.2%, 99.1%) for COVID-19-related admissions and underestimated COVID-19 attributable hospital days. The Massachusetts classification had a sensitivity of 60.5% (519/858, 95% CI 57.2%, 63.8%) and specificity of 78.6% (623/793, 95% CI 75.7%, 81.4%) for COVID-19-related admissions, underestimating total number of hospital and ICU bed days while overestimating COVID-19-related intubations, ICU admissions, and deaths. CONCLUSION: Half of SARS-CoV-2 hospitalizations were for COVID-19 during the Omicron wave. The CDC algorithm was more specific and sensitive than the Massachusetts classification, but underestimated the burden of COVID-19 admissions. TRIAL REGISTRATION: Clinicaltrials.gov, NCT04702945.
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spelling pubmed-105220232023-09-27 Comparing methods to classify admitted patients with SARS-CoV-2 as admitted for COVID-19 versus with incidental SARS-CoV-2: A cohort study Hohl, Corinne M. Cragg, Amber Purssel, Elizabeth McAlister, Finlay A. Ting, Daniel K. Scheuermeyer, Frank Stachura, Maja Grant, Lars Taylor, John Kanu, Josephine Hau, Jeffrey P. Cheng, Ivy Atzema, Clare L. Bola, Rajan Morrison, Laurie J. Landes, Megan Perry, Jeffrey J. Rosychuk, Rhonda J. PLoS One Research Article INTRODUCTION: Not all patients with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection develop symptomatic coronavirus disease 2019 (COVID-19), making it challenging to assess the burden of COVID-19-related hospitalizations and mortality. We aimed to determine the proportion, resource utilization, and outcomes of SARS-CoV-2 positive patients admitted for COVID-19, and assess the impact of using the Center for Disease Control’s (CDC) discharge diagnosis-based algorithm and the Massachusetts state department’s drug administration-based classification system on identifying admissions for COVID-19. METHODS: In this retrospective cohort study, we enrolled consecutive SARS-CoV-2 positive patients admitted to one of five hospitals in British Columbia between December 19, 2021 and May 31,2022. We completed medical record reviews, and classified hospitalizations as being primarily for COVID-19 or with incidental SARS-CoV-2 infection. We applied the CDC algorithm and the Massachusetts classification to estimate the difference in hospital days, intensive care unit (ICU) days and in-hospital mortality and calculated sensitivity and specificity. RESULTS: Of 42,505 Emergency Department patients, 1,651 were admitted and tested positive for SARS-CoV-2, with 858 (52.0%, 95% CI 49.6–54.4) admitted for COVID-19. Patients hospitalized for COVID-19 required ICU admission (14.0% versus 8.2%, p<0.001) and died (12.6% versus 6.4%, p<0.001) more frequently compared with patients with incidental SARS-CoV-2. Compared to case classification by clinicians, the CDC algorithm had a sensitivity of 82.9% (711/858, 95% CI 80.3%, 85.4%) and specificity of 98.1% (778/793, 95% CI 97.2%, 99.1%) for COVID-19-related admissions and underestimated COVID-19 attributable hospital days. The Massachusetts classification had a sensitivity of 60.5% (519/858, 95% CI 57.2%, 63.8%) and specificity of 78.6% (623/793, 95% CI 75.7%, 81.4%) for COVID-19-related admissions, underestimating total number of hospital and ICU bed days while overestimating COVID-19-related intubations, ICU admissions, and deaths. CONCLUSION: Half of SARS-CoV-2 hospitalizations were for COVID-19 during the Omicron wave. The CDC algorithm was more specific and sensitive than the Massachusetts classification, but underestimated the burden of COVID-19 admissions. TRIAL REGISTRATION: Clinicaltrials.gov, NCT04702945. Public Library of Science 2023-09-26 /pmc/articles/PMC10522023/ /pubmed/37751455 http://dx.doi.org/10.1371/journal.pone.0291580 Text en © 2023 Hohl et al https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Article
Hohl, Corinne M.
Cragg, Amber
Purssel, Elizabeth
McAlister, Finlay A.
Ting, Daniel K.
Scheuermeyer, Frank
Stachura, Maja
Grant, Lars
Taylor, John
Kanu, Josephine
Hau, Jeffrey P.
Cheng, Ivy
Atzema, Clare L.
Bola, Rajan
Morrison, Laurie J.
Landes, Megan
Perry, Jeffrey J.
Rosychuk, Rhonda J.
Comparing methods to classify admitted patients with SARS-CoV-2 as admitted for COVID-19 versus with incidental SARS-CoV-2: A cohort study
title Comparing methods to classify admitted patients with SARS-CoV-2 as admitted for COVID-19 versus with incidental SARS-CoV-2: A cohort study
title_full Comparing methods to classify admitted patients with SARS-CoV-2 as admitted for COVID-19 versus with incidental SARS-CoV-2: A cohort study
title_fullStr Comparing methods to classify admitted patients with SARS-CoV-2 as admitted for COVID-19 versus with incidental SARS-CoV-2: A cohort study
title_full_unstemmed Comparing methods to classify admitted patients with SARS-CoV-2 as admitted for COVID-19 versus with incidental SARS-CoV-2: A cohort study
title_short Comparing methods to classify admitted patients with SARS-CoV-2 as admitted for COVID-19 versus with incidental SARS-CoV-2: A cohort study
title_sort comparing methods to classify admitted patients with sars-cov-2 as admitted for covid-19 versus with incidental sars-cov-2: a cohort study
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10522023/
https://www.ncbi.nlm.nih.gov/pubmed/37751455
http://dx.doi.org/10.1371/journal.pone.0291580
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