Dynamic Changes in Parameters of Complete Blood Count Predict Disease Severity and Prognosis in Patients with COVID-19; A Prospective Study
Background: The pandemic of the coronavirus disease 2019 (COVID-19) is a major cause of death worldwide; thus, disease prediction is important. This study aimed to evaluate dynamic changes of complete blood count parameters in adult patients to predict disease severity. Materials and Methods: Data...
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Shahid Beheshti University of Medical Sciences
2025-01-01
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| Series: | Novelty in Biomedicine |
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| Online Access: | https://journals.sbmu.ac.ir/nbm/article/view/45941 |
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| author | Toktam Alirezaei Mahdi Baratnia Rama Bozorgmehr Yasamansadat Keshmiri Faezeh Ebrahimpour Maryam Arefnia Mohammadali Ghodsirad |
| author_facet | Toktam Alirezaei Mahdi Baratnia Rama Bozorgmehr Yasamansadat Keshmiri Faezeh Ebrahimpour Maryam Arefnia Mohammadali Ghodsirad |
| author_sort | Toktam Alirezaei |
| collection | DOAJ |
| description | Background: The pandemic of the coronavirus disease 2019 (COVID-19) is a major cause of death worldwide; thus, disease prediction is important. This study aimed to evaluate dynamic changes of complete blood count parameters in adult patients to predict disease severity.
Materials and Methods: Data from 980 consecutive hospitalized patients diagnosed with COVID-19 were analyzed prospectively. Patients were categorized into moderate disease-cured (n = 682), severe disease-cured (n = 136), and deceased (n = 162) groups. Clinical conditions at the admission and blood samples every other day were collected for each patient from hospital admission to discharge or death. Mean values of serum parameters were compared among the three groups; the Hazard ratio of different indices for death was calculated, and repeated measured ANOVA was employed to assess the prognostic importance of dynamic changes in blood parameters during the disease.
Results: Univariable and multivariable regression analysis showed that the only important clinical risk factor associated with death was needing invasive ventilation at admission (HR of 18.97 and 23.82 in univariable and multivariable regression analysis, respectively). Considering dynamic changes in blood elements, repeated measured ANOVA showed patients who survived had a decrease in WBC and Neutrophil count as well as Neutrophil to lymphocyte ratio (NLR) compared to expired patients; in contrast, platelet and lymphocyte count increased in survivors while dropped in deceased ones.
Conclusion: Dynamic changes in blood indices are prognostic indicators of an unfavorable prognosis for COVID-19 infection. |
| format | Article |
| id | doaj-art-a98b4267bb6e4a6a851351245bc585f5 |
| institution | Kabale University |
| issn | 2345-3907 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | Shahid Beheshti University of Medical Sciences |
| record_format | Article |
| series | Novelty in Biomedicine |
| spelling | doaj-art-a98b4267bb6e4a6a851351245bc585f52025-01-20T05:01:18ZengShahid Beheshti University of Medical SciencesNovelty in Biomedicine2345-39072025-01-0113110.22037/nbm.v13i1.4594135835Dynamic Changes in Parameters of Complete Blood Count Predict Disease Severity and Prognosis in Patients with COVID-19; A Prospective StudyToktam Alirezaei0Mahdi Baratnia1Rama Bozorgmehr2Yasamansadat Keshmiri3Faezeh Ebrahimpour4Maryam Arefnia5Mohammadali Ghodsirad61Men's Health and Reproductive Health Research Center, Shahid Beheshti University of Medical Sciences, Tehran, Iran1Men's Health and Reproductive Health Research Center, Shahid Beheshti University of Medical Sciences, Tehran, Iran2Clinical Research Development Unit of Shohada Tajrish Hospital, Shahid Beheshti University of Medical Sciences, Tehran, Iran3School of Medicine, Shahid Beheshti University of Medical Sciences, Tehran, Iran3School of Medicine, Shahid Beheshti University of Medical Sciences, Tehran, Iran1Men's Health and Reproductive Health Research Center, Shahid Beheshti University of Medical Sciences, Tehran, Iran1Men's Health and Reproductive Health Research Center, Shahid Beheshti University of Medical Sciences, Tehran, Iran, 3School of Medicine, Shahid Beheshti University of Medical Sciences, Tehran, IranBackground: The pandemic of the coronavirus disease 2019 (COVID-19) is a major cause of death worldwide; thus, disease prediction is important. This study aimed to evaluate dynamic changes of complete blood count parameters in adult patients to predict disease severity. Materials and Methods: Data from 980 consecutive hospitalized patients diagnosed with COVID-19 were analyzed prospectively. Patients were categorized into moderate disease-cured (n = 682), severe disease-cured (n = 136), and deceased (n = 162) groups. Clinical conditions at the admission and blood samples every other day were collected for each patient from hospital admission to discharge or death. Mean values of serum parameters were compared among the three groups; the Hazard ratio of different indices for death was calculated, and repeated measured ANOVA was employed to assess the prognostic importance of dynamic changes in blood parameters during the disease. Results: Univariable and multivariable regression analysis showed that the only important clinical risk factor associated with death was needing invasive ventilation at admission (HR of 18.97 and 23.82 in univariable and multivariable regression analysis, respectively). Considering dynamic changes in blood elements, repeated measured ANOVA showed patients who survived had a decrease in WBC and Neutrophil count as well as Neutrophil to lymphocyte ratio (NLR) compared to expired patients; in contrast, platelet and lymphocyte count increased in survivors while dropped in deceased ones. Conclusion: Dynamic changes in blood indices are prognostic indicators of an unfavorable prognosis for COVID-19 infection.https://journals.sbmu.ac.ir/nbm/article/view/45941covid-19severityblood cell countmortalityintensive care units |
| spellingShingle | Toktam Alirezaei Mahdi Baratnia Rama Bozorgmehr Yasamansadat Keshmiri Faezeh Ebrahimpour Maryam Arefnia Mohammadali Ghodsirad Dynamic Changes in Parameters of Complete Blood Count Predict Disease Severity and Prognosis in Patients with COVID-19; A Prospective Study Novelty in Biomedicine covid-19 severity blood cell count mortality intensive care units |
| title | Dynamic Changes in Parameters of Complete Blood Count Predict Disease Severity and Prognosis in Patients with COVID-19; A Prospective Study |
| title_full | Dynamic Changes in Parameters of Complete Blood Count Predict Disease Severity and Prognosis in Patients with COVID-19; A Prospective Study |
| title_fullStr | Dynamic Changes in Parameters of Complete Blood Count Predict Disease Severity and Prognosis in Patients with COVID-19; A Prospective Study |
| title_full_unstemmed | Dynamic Changes in Parameters of Complete Blood Count Predict Disease Severity and Prognosis in Patients with COVID-19; A Prospective Study |
| title_short | Dynamic Changes in Parameters of Complete Blood Count Predict Disease Severity and Prognosis in Patients with COVID-19; A Prospective Study |
| title_sort | dynamic changes in parameters of complete blood count predict disease severity and prognosis in patients with covid 19 a prospective study |
| topic | covid-19 severity blood cell count mortality intensive care units |
| url | https://journals.sbmu.ac.ir/nbm/article/view/45941 |
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