OBJECTIVES: Severe forms of coronavirus disease 2019 (COVID-19) are characterized by an excessive production of inflammatory cytokines. Activated monocytes secrete high levels of cytokines. Human monocytes are divided into three major populations: conventional (CD14posCD16neg), non-classical (CD14dimCD16pos), and intermediate (CD14posCD16pos) monocytes. The aim of this study was to analyze whether the distribution of conventional (CD16neg) and CD16pos monocytes is different in patients with COVID-19 and whether the variations could be predictive of the outcome of the disease. METHODS: We performed a prospective study on 390 consecutive patients referred to the Emergency Unit, with a proven diagnosis of SARS-CoV 2 infection by RT-PCR. Using the CytoDiff™ reagent, an automated routine leukocyte differential, we quantified CD16neg and CD16pos monocytes. RESULTS: In the entire population, median CD16neg and CD16pos monocyte levels (0.398 and 0.054×109/L, respectively) were in the normal range [(0.3-0.7×109/L) and (0.015-0.065×109/L), respectively], but the 35 patients in the intensive care unit (ICU) had a significantly (p<0.001) lower CD16pos monocyte count (0.018 × 109/L) in comparison to the 70 patients who were discharged (0.064 × 109/L) or were hospitalized in conventional units (0.058 × 109/L). By ROC curve analysis, the ratio [absolute neutrophil count/CD16pos monocyte count] was highly discriminant to identify patients requiring ICU hospitalization: with a cut-off 193.1, the sensitivity and the specificity were 74.3 and 81.8%, respectively (area under the curve=0.817). CONCLUSIONS: Quantification of CD16pos monocytes and the ratio [absolute neutrophil count/CD16pos monocyte count] could constitute a marker of the severity of disease in COVID-19 patients.
OBJECTIVES: Severe forms of coronavirus disease 2019 (COVID-19) are characterized by an excessive production of inflammatory cytokines. Activated monocytes secrete high levels of cytokines. Human monocytes are divided into three major populations: conventional (CD14posCD16neg), non-classical (CD14dimCD16pos), and intermediate (CD14posCD16pos) monocytes. The aim of this study was to analyze whether the distribution of conventional (CD16neg) and CD16pos monocytes is different in patients with COVID-19 and whether the variations could be predictive of the outcome of the disease. METHODS: We performed a prospective study on 390 consecutive patients referred to the Emergency Unit, with a proven diagnosis of SARS-CoV 2 infection by RT-PCR. Using the CytoDiff™ reagent, an automated routine leukocyte differential, we quantified CD16neg and CD16pos monocytes. RESULTS: In the entire population, median CD16neg and CD16pos monocyte levels (0.398 and 0.054×109/L, respectively) were in the normal range [(0.3-0.7×109/L) and (0.015-0.065×109/L), respectively], but the 35 patients in the intensive care unit (ICU) had a significantly (p<0.001) lower CD16pos monocyte count (0.018 × 109/L) in comparison to the 70 patients who were discharged (0.064 × 109/L) or were hospitalized in conventional units (0.058 × 109/L). By ROC curve analysis, the ratio [absolute neutrophil count/CD16pos monocyte count] was highly discriminant to identify patients requiring ICU hospitalization: with a cut-off 193.1, the sensitivity and the specificity were 74.3 and 81.8%, respectively (area under the curve=0.817). CONCLUSIONS: Quantification of CD16pos monocytes and the ratio [absolute neutrophil count/CD16pos monocyte count] could constitute a marker of the severity of disease in COVID-19patients.
Authors: David Haschka; Verena Petzer; Francesco Robert Burkert; Gernot Fritsche; Sophie Wildner; Rosa Bellmann-Weiler; Piotr Tymoszuk; Guenter Weiss Journal: Eur J Immunol Date: 2022-05-06 Impact factor: 6.688
Authors: Anita Pirabe; Stefan Heber; Waltraud C Schrottmaier; Anna Schmuckenschlager; Sonja Treiber; David Pereyra; Jonas Santol; Erich Pawelka; Marianna Traugott; Christian Schörgenhofer; Tamara Seitz; Mario Karolyi; Bernd Jilma; Ulrike Resch; Alexander Zoufaly; Alice Assinger Journal: Cells Date: 2021-11-30 Impact factor: 6.600