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Characterising biological mechanisms underlying ethnicity-associated outcomes in COVID-19 through biomarker trajectories: a multicentre registry analysis
BACKGROUND: Differences in routinely collected biomarkers between ethnic groups could reflect dysregulated host responses to disease and to treatments, and be associated with excess morbidity and mortality in COVID-19. METHODS: A multicentre registry analysis from patients aged ≥16 yr with SARS-CoV-...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10121108/ https://www.ncbi.nlm.nih.gov/pubmed/37198030 http://dx.doi.org/10.1016/j.bja.2023.04.008 |
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author | Wan, Yize I. Puthucheary, Zudin A. Pearse, Rupert M. Prowle, John R. |
author_facet | Wan, Yize I. Puthucheary, Zudin A. Pearse, Rupert M. Prowle, John R. |
author_sort | Wan, Yize I. |
collection | PubMed |
description | BACKGROUND: Differences in routinely collected biomarkers between ethnic groups could reflect dysregulated host responses to disease and to treatments, and be associated with excess morbidity and mortality in COVID-19. METHODS: A multicentre registry analysis from patients aged ≥16 yr with SARS-CoV-2 infection and emergency admission to Barts Health NHS Trust hospitals during January 1, 2020 to May 13, 2020 (wave 1) and September 1, 2020 to February 17, 2021 (wave 2) was subjected to unsupervised longitudinal clustering techniques to identify distinct phenotypic patient clusters based on trajectories of routine blood results over the first 15 days of hospital admission. Distribution of trajectory clusters across ethnic categories was determined, and associations between ethnicity, trajectory clusters, and 30-day survival were assessed using multivariable Cox proportional hazards modelling. Secondary outcomes were ICU admission, survival to hospital discharge, and long-term survival to 640 days. RESULTS: We included 3237 patients with hospital length of stay ≥7 days. In patients who died, there was greater representation of Black and Asian ethnicity in trajectory clusters for C-reactive protein and urea-to-creatinine ratio associated with increased risk of death. Inclusion of trajectory clusters in survival analyses attenuated or abrogated the higher risk of death in Asian and Black patients. Inclusion of C-reactive protein went from hazard ratio (HR) 1.36 [0.95–1.94] to HR 0.97 [0.59–1.59] (wave 1), and from HR 1.42 [1.15–1.75]) to HR 1.04 [0.78–1.39] (wave 2) in Asian patients. Trajectory clusters associated with reduced 30-day survival were similarly associated with worse secondary outcomes. CONCLUSIONS: Clinical biochemical monitoring of COVID-19 and progression and treatment response in SARS-CoV-2 infection should be interpreted in the context of ethnic background. |
format | Online Article Text |
id | pubmed-10121108 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Elsevier |
record_format | MEDLINE/PubMed |
spelling | pubmed-101211082023-04-24 Characterising biological mechanisms underlying ethnicity-associated outcomes in COVID-19 through biomarker trajectories: a multicentre registry analysis Wan, Yize I. Puthucheary, Zudin A. Pearse, Rupert M. Prowle, John R. Br J Anaesth Critical Care BACKGROUND: Differences in routinely collected biomarkers between ethnic groups could reflect dysregulated host responses to disease and to treatments, and be associated with excess morbidity and mortality in COVID-19. METHODS: A multicentre registry analysis from patients aged ≥16 yr with SARS-CoV-2 infection and emergency admission to Barts Health NHS Trust hospitals during January 1, 2020 to May 13, 2020 (wave 1) and September 1, 2020 to February 17, 2021 (wave 2) was subjected to unsupervised longitudinal clustering techniques to identify distinct phenotypic patient clusters based on trajectories of routine blood results over the first 15 days of hospital admission. Distribution of trajectory clusters across ethnic categories was determined, and associations between ethnicity, trajectory clusters, and 30-day survival were assessed using multivariable Cox proportional hazards modelling. Secondary outcomes were ICU admission, survival to hospital discharge, and long-term survival to 640 days. RESULTS: We included 3237 patients with hospital length of stay ≥7 days. In patients who died, there was greater representation of Black and Asian ethnicity in trajectory clusters for C-reactive protein and urea-to-creatinine ratio associated with increased risk of death. Inclusion of trajectory clusters in survival analyses attenuated or abrogated the higher risk of death in Asian and Black patients. Inclusion of C-reactive protein went from hazard ratio (HR) 1.36 [0.95–1.94] to HR 0.97 [0.59–1.59] (wave 1), and from HR 1.42 [1.15–1.75]) to HR 1.04 [0.78–1.39] (wave 2) in Asian patients. Trajectory clusters associated with reduced 30-day survival were similarly associated with worse secondary outcomes. CONCLUSIONS: Clinical biochemical monitoring of COVID-19 and progression and treatment response in SARS-CoV-2 infection should be interpreted in the context of ethnic background. Elsevier 2023-09 2023-04-21 /pmc/articles/PMC10121108/ /pubmed/37198030 http://dx.doi.org/10.1016/j.bja.2023.04.008 Text en © 2023 The Author(s) https://creativecommons.org/licenses/by/4.0/This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Critical Care Wan, Yize I. Puthucheary, Zudin A. Pearse, Rupert M. Prowle, John R. Characterising biological mechanisms underlying ethnicity-associated outcomes in COVID-19 through biomarker trajectories: a multicentre registry analysis |
title | Characterising biological mechanisms underlying ethnicity-associated outcomes in COVID-19 through biomarker trajectories: a multicentre registry analysis |
title_full | Characterising biological mechanisms underlying ethnicity-associated outcomes in COVID-19 through biomarker trajectories: a multicentre registry analysis |
title_fullStr | Characterising biological mechanisms underlying ethnicity-associated outcomes in COVID-19 through biomarker trajectories: a multicentre registry analysis |
title_full_unstemmed | Characterising biological mechanisms underlying ethnicity-associated outcomes in COVID-19 through biomarker trajectories: a multicentre registry analysis |
title_short | Characterising biological mechanisms underlying ethnicity-associated outcomes in COVID-19 through biomarker trajectories: a multicentre registry analysis |
title_sort | characterising biological mechanisms underlying ethnicity-associated outcomes in covid-19 through biomarker trajectories: a multicentre registry analysis |
topic | Critical Care |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10121108/ https://www.ncbi.nlm.nih.gov/pubmed/37198030 http://dx.doi.org/10.1016/j.bja.2023.04.008 |
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