Journal of Cardiovascular Emergencies (Jun 2024)

The Prognostic Role of Neutrophil-to-Lymphocyte Ratio, Monocyte-to-Lymphocyte Ratio, and Platelet-to-Lymphocyte Ratio in the Risk of Major Adverse Cardiovascular Events and Mortality in Patients with COVID-19: a State-of-the-Art Review

  • Arbănași Eliza Mihaela,
  • Russu Eliza

DOI
https://doi.org/10.2478/jce-2024-0010
Journal volume & issue
Vol. 10, no. 2
pp. 61 – 70

Abstract

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Coronavirus disease (COVID-19) is a viral infection caused by SARS-CoV-2 that has become a global health emergency with a negative impact on patient care. The evolution of patients with COVID-19 is unpredictable, with an unfavorable evolution in the case of patients with comorbidities. This state-of-the-art review focuses on the role of hematological inflammatory biomarkers: the neutrophil-to-lymphocyte ratio (NLR), monocyte-to-lymphocyte ratio (MLR), and platelet-to-lymphocyte ratio (PLR) in predicting major adverse cardiovascular events (MACE) and mortality in patients with COVID-19. In this review, we included 21 studies that investigated the role of biomarkers in the risk of mortality and MACE, reporting on a total of 7,588 patients. Regarding the clinical data, 57.49% of the patients presented hypertension (15 out of the 21 studies reported hypertensive patients), followed by ischemic heart disease in 33.56% of patients (13 studies) and diabetes in 30.37% of patients (17 studies). In additional, among the usual risk factors, 23.55% of patients presented obesity (7 studies) and 23.02% were active smokers (10 studies). We recorded an average cut-off value of 7.728 for NLR (range 2.6973–15.2), 0.594 for MLR (range 0.26–0.81), and 215.07 for PLR (range 177.51–266.9) for the risk of MACE and mortality. We also recorded an average area under the curve (AUC) of 0.783 for NLR, 0.744 for MLR, and 0.713 for PLR. Our findings suggest that these biomarkers exhibit prognostic value in predicting adverse outcomes, and that evaluating these biomarkers at admission could provide novel information in stratifying risk groups for improving patient management.

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