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Review
. 2019;15(4):274-282.
doi: 10.2174/1573403X15666190225123544.

Hematological Parameters as Prognostic Biomarkers in Patients with Cardiovascular Diseases

José Gildo de Moura Monteiro Júnior  1 , Dilênia de Oliveira Cipriano Torres  2 , Dário Celestino Sobral Filho  3
Affiliations
Review

Hematological Parameters as Prognostic Biomarkers in Patients with Cardiovascular Diseases

José Gildo de Moura Monteiro Júnior et al. Curr Cardiol Rev. 2019.

Abstract

Cardiovascular diseases are the major causes of preventable health loss from disease in the world and lead to functional disturbances including hematological parameters. The inflammatory and hypoxemic nature of cardiovascular diseases causes a stimulus in the bone marrow and, depending on the intensity of this stimulus, there is a release of immature cells or increase of other cells in the bloodstream. Therefore, their presence in the circulation is an important variable used to diagnose, stratify and predict diseases. In the last five decades, with the advent of automated counting of immature cells in the peripheral blood, the hemogram was transformed into a clinical tool of great importance in hospital surveillance for demonstrating this daily variability in the hematopoietic response according to the existing injury in the patient. Studies have shown that the presence of nucleated red blood cells and increases in mean platelet volume, immature granulocytes and neutrophil to lymphocyte ratio in the systemic circulation are independent prognostic biomarkers. This review article has as main objective to demonstrate the association of these hematological parameters to cardiovascular diseases, emphasizing their importance in clinical decision making.

Keywords: Nucleated red blood cells; biomarkers; cardiovascular diseases; immature granulocytes; mean platelet volume; neutrophil to lymphocyte ratio..

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Figures

Fig. (1)
Fig. (1)
Formation of blood cell differences from pluripotent hematopoietic stem cell (PHSC) in bone marrow.
Fig. (2)
Fig. (2)
comparison of the ROC curves, p = 0.01.
Fig. (3)
Fig. (3)
Kaplan-Meier curve for mortality (death). Patients categorized by platelet count during the period of hospital stay (days).
See this image and copyright information in PMC

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