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Author Spotlight: Advancing Immune Monitoring in Critical Care Patients Using Whole Blood Assays
Published on: September 20, 2024
Hematological changes in SARS-COV-2 positive patients
Mafalda Urbano1, Elísio Costa2, Catarina Geraldes1
1Coimbra University Hospital Center, Coimbra, Portugal.
Introduction:
The novel SARS-CoV-2 infection has been spreading around the world since January 2020 causing the Corona Virus Disease 2019. Leukopenia, lymphopenia and hypercoagulability with elevated D- Dimers have been described in COVID-19 patients to date. This study aimed to clarify if some blood parameters can be used as biomarkers to facilitate diagnosis and establish prognosis. Methods: We selected patients who had tested positive for SARS-CoV-2 and had had a hemogram performed between the March 15 and April 15, 2020. Socio-demographic and analytical data were obtained from 274 patients at admission in two Portuguese public hospitals. We then analyzed the hemogram parameters at admission in the intensive care and collected data on patient survival during the SARS-CoV-2 disease follow-up. The data were analyzed using appropriate statistical tests. Results: Patients requiring the intensive care unit (ICU) present an increase in leukocytes and neutrophils (+3.1 × 109/L and +6.4 × 109/L, respectively), a lymphocyte decrease and a platelet rise (-1.6 × 109/L and +60.8 × 109/L, respectively). The erythrocytes, hemoglobin and median globular volume tend to decrease (-0.5 × 1012, - 1.2 g/dL; -3 fL, respectively). The lactic acid dehydrogenase (LDH) at admission was significantly higher (+58.1 U/L). The age, sex, platelets, lymphocyte count neutrophil counts, neutrophil/lymphocyte ratio, erythrocytes and cell hemoglobin concentration mean (CHCM) are independently associated with mortality (odds ratio (OR) = 0.046, p < 0.001; OR = 0.2364, p = 0.045; OR = 9.106, p = 0.001; OR = 0.194, p = 0.033; OR = 0.062, p = 0.003; OR = 0.098, p = 0.002; OR = 9.021, p < 0.001; OR = 7.016, p = 0.007, respectively).
Conclusion:
The hematological data at admission in the health care system can predict the mortality of the SARS-CoV-2 infection and we recommend its use in the clinical decisions and patient prognosis evaluation.
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