Liu, A; Hammond, R; Donnelly, PD; Kaski, JC; Coates, AR
(2023)
Effective prognostic and clinical risk stratification in COVID-19 using multimodality biomarkers.
J Intern Med, 294 (1).
pp. 21-46.
ISSN 1365-2796
https://doi.org/10.1111/joim.13646
SGUL Authors: Coates, Anthony Robert Milnes
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Abstract
In acute COVID-19 patients, effective clinical risk stratification has important implications on treatment and therapeutic resource distribution. This article reviews the evidence behind a wide range of biomarkers with prognostic value in COVID-19. Patient characteristics and co-morbidities, such as cardiovascular and respiratory diseases, are associated with increased mortality risk. Peripheral oxygen saturation and arterial oxygenation are predictive of severe respiratory compromise, whilst risk scores such as the 4C-Score enable multi-factorial prognostic risk estimation. Blood tests such as markers of inflammation, cardiac injury and D-dimer, and abnormalities on electrocardiogram are linked to inpatient prognosis. Of the imaging modalities, lung ultrasound and echocardiography enable bedside assessment of prognostic abnormalities in COVID-19. Chest radiograph (CXR) and computed tomography (CT) can inform about prognostic pulmonary pathologies, whilst cardiovascular CT detects high-risk features such as coronary artery and aortic calcification. Dynamic changes in biomarkers, such as blood tests, CXR, CT and ECG findings, can further inform about disease severity and prognosis. Despite the vast volumes of existing evidence, several gaps exist in our understanding of COVID-19 biomarkers. Firstly, the pathophysiological basis on which these markers can foretell prognosis in COVID-19 remains poorly understood. Secondly, certain under-explored tests such as thoracic impedance assessment and cardiovascular magnetic resonance imaging deserve further investigation. Lastly, the prognostic value of most biomarkers in COVID-19 are derived from retrospective analyses. Prospectively studies are required to validate these markers for guiding clinical decision-making and to facilitate their translation into clinical management pathways. This article is protected by copyright. All rights reserved.
Item Type: | Article | ||||||||
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Additional Information: | © 2023 The Authors. Journal of Internal Medicine published by John Wiley & Sons Ltd on behalf of Association for Publication of The Journal of Internal Medicine. This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited. | ||||||||
Keywords: | COVID-19, biomarker, clinical outcomes, diagnostic performance, prognosis, risk stratification, biomarker, clinical outcomes, COVID-19, diagnostic performance, prognosis, risk stratification, 1103 Clinical Sciences, Cardiovascular System & Hematology | ||||||||
SGUL Research Institute / Research Centre: | Academic Structure > Infection and Immunity Research Institute (INII) | ||||||||
Journal or Publication Title: | J Intern Med | ||||||||
ISSN: | 1365-2796 | ||||||||
Language: | eng | ||||||||
Dates: |
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Publisher License: | Creative Commons: Attribution 4.0 | ||||||||
PubMed ID: | 37106509 | ||||||||
Go to PubMed abstract | |||||||||
URI: | https://openaccess.sgul.ac.uk/id/eprint/115390 | ||||||||
Publisher's version: | https://doi.org/10.1111/joim.13646 |
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