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Identifying pre-existing conditions and multimorbidity patterns associated with in-hospital mortality in patients with COVID-19

We investigated the association between a wide range of comorbidities and COVID-19 in-hospital mortality and assessed the influence of multi morbidity on the risk of COVID-19-related death using a large, regional cohort of 6036 hospitalized patients. This retrospective cohort study was conducted usi...

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Autores principales: Bucholc, Magda, Bradley, Declan, Bennett, Damien, Patterson, Lynsey, Spiers, Rachel, Gibson, David, Van Woerden, Hugo, Bjourson, Anthony J.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9568958/
https://www.ncbi.nlm.nih.gov/pubmed/36243878
http://dx.doi.org/10.1038/s41598-022-20176-w
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author Bucholc, Magda
Bradley, Declan
Bennett, Damien
Patterson, Lynsey
Spiers, Rachel
Gibson, David
Van Woerden, Hugo
Bjourson, Anthony J.
author_facet Bucholc, Magda
Bradley, Declan
Bennett, Damien
Patterson, Lynsey
Spiers, Rachel
Gibson, David
Van Woerden, Hugo
Bjourson, Anthony J.
author_sort Bucholc, Magda
collection PubMed
description We investigated the association between a wide range of comorbidities and COVID-19 in-hospital mortality and assessed the influence of multi morbidity on the risk of COVID-19-related death using a large, regional cohort of 6036 hospitalized patients. This retrospective cohort study was conducted using Patient Administration System Admissions and Discharges data. The International Classification of Diseases 10th edition (ICD-10) diagnosis codes were used to identify common comorbidities and the outcome measure. Individuals with lymphoma (odds ratio [OR], 2.78;95% CI,1.64–4.74), metastatic cancer (OR, 2.17; 95% CI,1.25–3.77), solid tumour without metastasis (OR, 1.67; 95% CI,1.16–2.41), liver disease (OR: 2.50, 95% CI,1.53–4.07), congestive heart failure (OR, 1.69; 95% CI,1.32–2.15), chronic obstructive pulmonary disease (OR, 1.43; 95% CI,1.18–1.72), obesity (OR, 5.28; 95% CI,2.92–9.52), renal disease (OR, 1.81; 95% CI,1.51–2.19), and dementia (OR, 1.44; 95% CI,1.17–1.76) were at increased risk of COVID-19 mortality. Asthma was associated with a lower risk of death compared to non-asthma controls (OR, 0.60; 95% CI,0.42–0.86). Individuals with two (OR, 1.79; 95% CI, 1.47–2.20; P < 0.001), and three or more comorbidities (OR, 1.80; 95% CI, 1.43–2.27; P < 0.001) were at increasingly higher risk of death when compared to those with no underlying conditions. Furthermore, multi morbidity patterns were analysed by identifying clusters of conditions in hospitalised COVID-19 patients using k-mode clustering, an unsupervised machine learning technique. Six patient clusters were identified, with recognisable co-occurrences of COVID-19 with different combinations of diseases, namely, cardiovascular (100%) and renal (15.6%) diseases in patient Cluster 1; mental and neurological disorders (100%) with metabolic and endocrine diseases (19.3%) in patient Cluster 2; respiratory (100%) and cardiovascular (15.0%) diseases in patient Cluster 3, cancer (5.9%) with genitourinary (9.0%) as well as metabolic and endocrine diseases (9.6%) in patient Cluster 4; metabolic and endocrine diseases (100%) and cardiovascular diseases (69.1%) in patient Cluster 5; mental and neurological disorders (100%) with cardiovascular diseases (100%) in patient Cluster 6. The highest mortality of 29.4% was reported in Cluster 6.
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spelling pubmed-95689582022-10-16 Identifying pre-existing conditions and multimorbidity patterns associated with in-hospital mortality in patients with COVID-19 Bucholc, Magda Bradley, Declan Bennett, Damien Patterson, Lynsey Spiers, Rachel Gibson, David Van Woerden, Hugo Bjourson, Anthony J. Sci Rep Article We investigated the association between a wide range of comorbidities and COVID-19 in-hospital mortality and assessed the influence of multi morbidity on the risk of COVID-19-related death using a large, regional cohort of 6036 hospitalized patients. This retrospective cohort study was conducted using Patient Administration System Admissions and Discharges data. The International Classification of Diseases 10th edition (ICD-10) diagnosis codes were used to identify common comorbidities and the outcome measure. Individuals with lymphoma (odds ratio [OR], 2.78;95% CI,1.64–4.74), metastatic cancer (OR, 2.17; 95% CI,1.25–3.77), solid tumour without metastasis (OR, 1.67; 95% CI,1.16–2.41), liver disease (OR: 2.50, 95% CI,1.53–4.07), congestive heart failure (OR, 1.69; 95% CI,1.32–2.15), chronic obstructive pulmonary disease (OR, 1.43; 95% CI,1.18–1.72), obesity (OR, 5.28; 95% CI,2.92–9.52), renal disease (OR, 1.81; 95% CI,1.51–2.19), and dementia (OR, 1.44; 95% CI,1.17–1.76) were at increased risk of COVID-19 mortality. Asthma was associated with a lower risk of death compared to non-asthma controls (OR, 0.60; 95% CI,0.42–0.86). Individuals with two (OR, 1.79; 95% CI, 1.47–2.20; P < 0.001), and three or more comorbidities (OR, 1.80; 95% CI, 1.43–2.27; P < 0.001) were at increasingly higher risk of death when compared to those with no underlying conditions. Furthermore, multi morbidity patterns were analysed by identifying clusters of conditions in hospitalised COVID-19 patients using k-mode clustering, an unsupervised machine learning technique. Six patient clusters were identified, with recognisable co-occurrences of COVID-19 with different combinations of diseases, namely, cardiovascular (100%) and renal (15.6%) diseases in patient Cluster 1; mental and neurological disorders (100%) with metabolic and endocrine diseases (19.3%) in patient Cluster 2; respiratory (100%) and cardiovascular (15.0%) diseases in patient Cluster 3, cancer (5.9%) with genitourinary (9.0%) as well as metabolic and endocrine diseases (9.6%) in patient Cluster 4; metabolic and endocrine diseases (100%) and cardiovascular diseases (69.1%) in patient Cluster 5; mental and neurological disorders (100%) with cardiovascular diseases (100%) in patient Cluster 6. The highest mortality of 29.4% was reported in Cluster 6. Nature Publishing Group UK 2022-10-15 /pmc/articles/PMC9568958/ /pubmed/36243878 http://dx.doi.org/10.1038/s41598-022-20176-w Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open Access This 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/) .
spellingShingle Article
Bucholc, Magda
Bradley, Declan
Bennett, Damien
Patterson, Lynsey
Spiers, Rachel
Gibson, David
Van Woerden, Hugo
Bjourson, Anthony J.
Identifying pre-existing conditions and multimorbidity patterns associated with in-hospital mortality in patients with COVID-19
title Identifying pre-existing conditions and multimorbidity patterns associated with in-hospital mortality in patients with COVID-19
title_full Identifying pre-existing conditions and multimorbidity patterns associated with in-hospital mortality in patients with COVID-19
title_fullStr Identifying pre-existing conditions and multimorbidity patterns associated with in-hospital mortality in patients with COVID-19
title_full_unstemmed Identifying pre-existing conditions and multimorbidity patterns associated with in-hospital mortality in patients with COVID-19
title_short Identifying pre-existing conditions and multimorbidity patterns associated with in-hospital mortality in patients with COVID-19
title_sort identifying pre-existing conditions and multimorbidity patterns associated with in-hospital mortality in patients with covid-19
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9568958/
https://www.ncbi.nlm.nih.gov/pubmed/36243878
http://dx.doi.org/10.1038/s41598-022-20176-w
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