Complement C5a and clinical markers as predictors of COVID-19 disease severity and mortality in a multi-ethnic population

Cyprian, FS, Suleman, M, Abdelhafez, I, Doudin, A, Masud Danjuma, IM, Mir, FA, Parray, A, Yousaf, Z, Siddiqui, MYA, Abdelmajid, A, Mulhim, M, Al-Shokri, S, Abukhattab, M, Shaheen, R, Elkord, E, Al-khal, AL, Elzouki, A-N and Girardi, G 2021, 'Complement C5a and clinical markers as predictors of COVID-19 disease severity and mortality in a multi-ethnic population' , Frontiers in Immunology, 12 , p. 707159.

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Abstract

Coronavirus disease-2019 (COVID-19) was declared as a pandemic by WHO in March 2020. SARS-CoV-2 causes a wide range of illness from asymptomatic to life-threatening. There is an essential need to identify biomarkers to predict disease severity and mortality during the earlier stages of the disease, aiding treatment and allocation of resources to improve survival. The aim of this study was to identify at the time of SARS-COV-2 infection patients at high risk of developing severe disease associated with low survival using blood parameters, including inflammation and coagulation mediators, vital signs, and pre-existing comorbidities. This cohort included 89 multi-ethnic COVID-19 patients recruited between July 14th and October 20th 2020 in Doha, Qatar. According to clinical severity, patients were grouped into severe (n=33), mild (n=33) and asymptomatic (n=23). Common routine tests such as complete blood count (CBC), glucose, electrolytes, liver and kidney function parameters and markers of inflammation, thrombosis and endothelial dysfunction including complement component split product C5a, Interleukin-6, ferritin and C-reactive protein were measured at the time COVID-19 infection was confirmed. Correlation tests suggest that C5a is a predictive marker of disease severity and mortality, in addition to 40 biological and physiological parameters that were found statistically significant between survivors and non-survivors. Survival analysis showed that high C5a levels, hypoalbuminemia, lymphopenia, elevated procalcitonin, neutrophilic leukocytosis, acute anemia along with increased acute kidney and hepatocellular injury markers were associated with a higher risk of death in COVID-19 patients. Altogether, we created a prognostic classification model, the CAL model (C5a, Albumin, and Lymphocyte count) to predict severity with significant accuracy. Stratification of patients using the CAL model could help in the identification of patients likely to develop severe symptoms in advance so that treatments can be targeted accordingly.

Item Type: Article
Contributors: Velu, V (Editor), Suryawanshi, G (Reviewer) and Sahoo, A (Reviewer)
Additional Information: ** From Frontiers via Jisc Publications Router ** Licence for this article: http://creativecommons.org/licenses/by/4.0/ **Journal IDs: eissn 1664-3224 **History: published_online 13-12-2021; accepted 19-11-2021; submitted 09-05-2021; collection 2021
Schools: Schools > School of Environment and Life Sciences > Biomedical Research Centre
Journal or Publication Title: Frontiers in Immunology
Publisher: Frontiers Media S.A.
ISSN: 1664-3224
Related URLs:
Funders: Qatar University
SWORD Depositor: Publications Router
Depositing User: Publications Router
Date Deposited: 06 Jan 2022 16:09
Last Modified: 15 Feb 2022 16:55
URI: https://usir.salford.ac.uk/id/eprint/62628

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