Neutrophil-to-lymphocyte ratio on admission to predict the severity and mortality of COVID-19 patients: A meta-analysis - 24/03/21
, Julius Calvin, BMedSci, Alya Darin Wijaya, BMedSci, Naufal Arkan Abiyyu Ibrahim, BMedSci
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Abstract |
Background |
The neutrophil-to-lymphocyte ratio (NLR), an inflammatory marker, was suggested to be predictive of severity and mortality in COVID-19 patients. Here, we investigated whether NLR levels on admission could predict the severity and mortality of COVID-19 patients.
Methods |
A literature search was conducted on 23 July 2020 to retrieve all published articles, including grey literature and preprints, investigating the association between on-admission NLR values and severity or mortality in COVID-19 patients. A meta-analysis was performed to determine the overall standardized mean difference (SMD) in NLR values and the pooled risk ratio (RR) for severity and mortality with the 95% Confidence Interval (95%CI).
Results |
A total of 38 articles, including 5699 patients with severity outcomes and 6033 patients with mortality outcomes, were included. The meta-analysis showed that severe and non-survivors of COVID-19 had higher on-admission NLR levels than non-severe and survivors (SMD 0.88; 95%CI 0.72–1.04; I2 = 75.52% and 1.87; 95%CI 1.25–2.49; I2 = 97.81%, respectively). Regardless of the different NLR cut-off values, the pooled mortality RR in patients with elevated vs. normal NLR levels was 2.74 (95%CI 0.98–7.66).
Conclusion |
High NLR levels on admission were associated with severe COVID-19 and mortality. Further studies need to focus on determining the optimal cut-off value for NLR before clinical use.
Il testo completo di questo articolo è disponibile in PDF.Highlights |
• | Neutrophil-to-lymphocyte ratio (NLR) is an accessible and cost-effective biomarker. |
• | High NLR on admission is associated with severe COVID-19 and mortality. |
• | NLR is recommended for use in resource-limited healthcare settings. |
Keywords : COVID-19, Neutrophil-to-lymphocyte ratio, Severity, Mortality, Meta-analysis
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