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Risk factors associated with severe hospital burden of COVID-19 disease in Regione Lombardia: a cohort study
BACKGROUND: Understanding the risk factors associated with hospital burden of COVID-19 is crucial for healthcare planning for any future waves of infection. METHODS: An observational cohort study is performed, using data on all PCR-confirmed cases of COVID-19 in Regione Lombardia, Italy, during the...
Autores principales: | , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8496148/ https://www.ncbi.nlm.nih.gov/pubmed/34620121 http://dx.doi.org/10.1186/s12879-021-06750-z |
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author | Presanis, Anne M. Kunzmann, Kevin Grosso, Francesca M. Jackson, Christopher H. Corbella, Alice Grasselli, Giacomo Salmoiraghi, Marco Gramegna, Maria De Angelis, Daniela Cereda, Danilo |
author_facet | Presanis, Anne M. Kunzmann, Kevin Grosso, Francesca M. Jackson, Christopher H. Corbella, Alice Grasselli, Giacomo Salmoiraghi, Marco Gramegna, Maria De Angelis, Daniela Cereda, Danilo |
author_sort | Presanis, Anne M. |
collection | PubMed |
description | BACKGROUND: Understanding the risk factors associated with hospital burden of COVID-19 is crucial for healthcare planning for any future waves of infection. METHODS: An observational cohort study is performed, using data on all PCR-confirmed cases of COVID-19 in Regione Lombardia, Italy, during the first wave of infection from February-June 2020. A multi-state modelling approach is used to simultaneously estimate risks of progression through hospital to final outcomes of either death or discharge, by pathway (via critical care or not) and the times to final events (lengths of stay). Logistic and time-to-event regressions are used to quantify the association of patient and population characteristics with the risks of hospital outcomes and lengths of stay respectively. RESULTS: Risks of severe outcomes such as ICU admission and mortality have decreased with month of admission (for example, the odds ratio of ICU admission in June vs March is 0.247 [0.120–0.508]) and increased with age (odds ratio of ICU admission in 45–65 vs 65 + age group is 0.286 [0.201–0.406]). Care home residents aged 65 + are associated with increased risk of hospital mortality and decreased risk of ICU admission. Being a healthcare worker appears to have a protective association with mortality risk (odds ratio of ICU mortality is 0.254 [0.143–0.453] relative to non-healthcare workers) and length of stay. Lengths of stay decrease with month of admission for survivors, but do not appear to vary with month for non-survivors. CONCLUSIONS: Improvements in clinical knowledge, treatment, patient and hospital management and public health surveillance, together with the waning of the first wave after the first lockdown, are hypothesised to have contributed to the reduced risks and lengths of stay over time. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12879-021-06750-z. |
format | Online Article Text |
id | pubmed-8496148 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-84961482021-10-08 Risk factors associated with severe hospital burden of COVID-19 disease in Regione Lombardia: a cohort study Presanis, Anne M. Kunzmann, Kevin Grosso, Francesca M. Jackson, Christopher H. Corbella, Alice Grasselli, Giacomo Salmoiraghi, Marco Gramegna, Maria De Angelis, Daniela Cereda, Danilo BMC Infect Dis Research BACKGROUND: Understanding the risk factors associated with hospital burden of COVID-19 is crucial for healthcare planning for any future waves of infection. METHODS: An observational cohort study is performed, using data on all PCR-confirmed cases of COVID-19 in Regione Lombardia, Italy, during the first wave of infection from February-June 2020. A multi-state modelling approach is used to simultaneously estimate risks of progression through hospital to final outcomes of either death or discharge, by pathway (via critical care or not) and the times to final events (lengths of stay). Logistic and time-to-event regressions are used to quantify the association of patient and population characteristics with the risks of hospital outcomes and lengths of stay respectively. RESULTS: Risks of severe outcomes such as ICU admission and mortality have decreased with month of admission (for example, the odds ratio of ICU admission in June vs March is 0.247 [0.120–0.508]) and increased with age (odds ratio of ICU admission in 45–65 vs 65 + age group is 0.286 [0.201–0.406]). Care home residents aged 65 + are associated with increased risk of hospital mortality and decreased risk of ICU admission. Being a healthcare worker appears to have a protective association with mortality risk (odds ratio of ICU mortality is 0.254 [0.143–0.453] relative to non-healthcare workers) and length of stay. Lengths of stay decrease with month of admission for survivors, but do not appear to vary with month for non-survivors. CONCLUSIONS: Improvements in clinical knowledge, treatment, patient and hospital management and public health surveillance, together with the waning of the first wave after the first lockdown, are hypothesised to have contributed to the reduced risks and lengths of stay over time. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12879-021-06750-z. BioMed Central 2021-10-07 /pmc/articles/PMC8496148/ /pubmed/34620121 http://dx.doi.org/10.1186/s12879-021-06750-z Text en © The Author(s) 2021 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data. |
spellingShingle | Research Presanis, Anne M. Kunzmann, Kevin Grosso, Francesca M. Jackson, Christopher H. Corbella, Alice Grasselli, Giacomo Salmoiraghi, Marco Gramegna, Maria De Angelis, Daniela Cereda, Danilo Risk factors associated with severe hospital burden of COVID-19 disease in Regione Lombardia: a cohort study |
title | Risk factors associated with severe hospital burden of COVID-19 disease in Regione Lombardia: a cohort study |
title_full | Risk factors associated with severe hospital burden of COVID-19 disease in Regione Lombardia: a cohort study |
title_fullStr | Risk factors associated with severe hospital burden of COVID-19 disease in Regione Lombardia: a cohort study |
title_full_unstemmed | Risk factors associated with severe hospital burden of COVID-19 disease in Regione Lombardia: a cohort study |
title_short | Risk factors associated with severe hospital burden of COVID-19 disease in Regione Lombardia: a cohort study |
title_sort | risk factors associated with severe hospital burden of covid-19 disease in regione lombardia: a cohort study |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8496148/ https://www.ncbi.nlm.nih.gov/pubmed/34620121 http://dx.doi.org/10.1186/s12879-021-06750-z |
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