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Predicting Disease Severity and Outcome in COVID-19 Patients: A Review of Multiple Biomarkers.

Tjendra Y,Al Mana AF,Espejo AP,Akgun Y,Millan NC,Gomez-Fernandez C,Cray C

Abstract

An abundance of clinical reports focused on specific laboratory parameters have been reported on coronavirus disease 19 (COVID-19), but a systematic analysis synthesizing these findings has not been performed.
To review and summarize the current available literature on the predictive role of various biomarkers in COVID-19 patients.
A literature search was performed using databases including PubMed, medRxiv, and bioRxiv. A total of 72 papers were reviewed, including 54 peer-reviewed papers and 18 non-peer-reviewed preprints.
Although the markers are considered nonspecific, acute-phase reactants, including C-reactive protein (CRP), ferritin, serum amyloid A (SAA), and procalcitonin, were reported as sensitive markers of acute COVID-19 disease. Significantly elevated white blood cell count; marked lymphopenia; decreased CD3, CD4, or CD8 T-lymphocyte counts; high neutrophil count; thrombocytopenia; and markedly elevated inflammatory biomarkers were associated with severe disease and the risk of developing sepsis with rapid progression. Trends observed by serial laboratory measurements during hospitalization, including progressive decrease of lymphocyte count, thrombocytopenia, elevated CRP, procalcitonin, increased liver enzymes, decreased renal function, and coagulation derangements, were more common in critically ill patient groups and associated with a high incidence of clinical complications. Elevated interleukin 6 level and markedly increased SAA were most often reported in severely and critically ill patients. Indicators of systemic inflammation, such as neutrophil to lymphocyte ratio, systemic immune-inflammation index, or COVID-19 Severity Score, may be used to predict disease severity, outcome, and mortality. Interpretation of the data reported in the studies reviewed here is limited because of the study design (mostly retrospective), limited sample size, and a lack of defined clinical criteria.

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