THE IMPACT OF HEMATOLOGICAL PARAMETERS ON SURVIVAL FOR PATIENTS WITH COVID-19
Objective: Coronavirus disease 2019 is an infectious disease caused by the novel severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Clinical and laboratory predictors may identification of patients at risk of mortality and guide treatment .To analyze laboratory abnormalities in patients w...
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| Auteurs principaux: | , , , , , , , , , |
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| Format: | article |
| Langue: | EN |
| Publié: |
Elsevier
2021
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| Sujets: | |
| Accès en ligne: | https://doaj.org/article/6666b030eae34e7dbaa3bbe3e3171e62 |
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| Résumé: | Objective: Coronavirus disease 2019 is an infectious disease caused by the novel severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Clinical and laboratory predictors may identification of patients at risk of mortality and guide treatment .To analyze laboratory abnormalities in patients with COVID-19 and define which parameters affect mortality and hospitalization Methodology: This retrospective study was conducted on 101 patients diagnosed with COVID-19. Demographic characteristics, laboratory parameters including complete blood count (CBC) parameters, biochemical tests, coagulation parameters, duration of hospitalization and final status (discharge or death) were recorded Results: Comparisons were made of survivors and non-survivors at the end of follow up period. Multivariate analysis showed mean platelet volume (MPV), platelet distribution width (PDW) and lactate dehydrogenase (LDH) to be significant predictors of mortality. The cut-off value of the hospitalization period was found to be 10 days, so patients were divided into two groups. In the multivariate models, no significant independent parameter was observed for the prediction of hospitalization duration. Conclusion: The results of the current study demonstrated that MPV, PDW and LDH were significant independent variables for the prediction of mortality. As SARS-CoV and SARS-CoV-2 are known to use the same receptor, there may be a similar structure and receptor for mutant variants and the first variant, so these predictive parameters can be considered to be as effective in mutant variants. |
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