Assessment of the relationship between hematologic parameters, (CPD), in screening for COVID-19 severity in women
Aims This study evaluated hematological parameters and cell population data (CPDs) to assess their ability to discriminate between moderate and severe COVID-19 in hospitalized female patients, and to identify potential markers associated with worse outcomes.Patients & methods A retrospective stu...
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| Main Authors: | , , , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Taylor & Francis Group
2025-12-01
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| Series: | Future Science OA |
| Subjects: | |
| Online Access: | https://www.tandfonline.com/doi/10.1080/20565623.2025.2540749 |
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| Summary: | Aims This study evaluated hematological parameters and cell population data (CPDs) to assess their ability to discriminate between moderate and severe COVID-19 in hospitalized female patients, and to identify potential markers associated with worse outcomes.Patients & methods A retrospective study was conducted on 84 adult female COVID-19 patients hospitalized at CHC-UFPR (Brazil) between March 2020 and July 2021. Patients were stratified into moderate (n = 46) and severe (n = 38) disease groups. A control group included 100 healthy female outpatients. Parameters analyzed included D-dimer, WBC count, neutrophil-to-lymphocyte ratio (NLR), and CPDs (LY-X, LY-Y). RT-qPCR was used for SARS-CoV-2 confirmation and variant identification.Results Significant differences (p < 0.05) in LY-X, LY-Y, NLR, and WBC were found between moderate and severe groups. D-dimer was elevated in severe cases. Among deceased patients (n = 17), WBC and NLR were markedly increased. ROC curve analysis confirmed the discriminatory power of these markers. No significant association was found between viral genotype and severity (p = 0.9602).Conclusions Hematological parameters, particularly CPDs and NLR, are valuable for early stratification of COVID-19 severity. These automated, rapid, and cost-effective measures can support clinical decision-making. However, CPD usage depends on analyzer availability and lacks standardization across platforms. |
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| ISSN: | 2056-5623 |