Blood Count and Renal Functionality Assessments in the Emergency Section Disclose Morbidity and Mortality in Omicron COVID-19 Patients: A Retrospective Study Article Swipe
YOU?
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· 2024
· Open Access
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· DOI: https://doi.org/10.3390/clinpract14030055
Background: SARS-CoV-2 is the coronavirus responsible for the COVID-19 pandemic. Even though we are no longer in a pandemic situation, people are still getting infected, some of them need hospitalization and a few of them die. Methods: We conducted a retrospective study including 445 patients who accessed the Emergency Section of Policlinico Umberto I, Rome, Italy, where they had routine blood exams. In this study, we focused on the complete blood count, serum creatinine and azotemia. The data were analyzed using ANOVA, Spearman correlation and ROC analyses. They were divided into four groups based on their clinical outcomes: (1) the emergency group (patients who had mild forms and were quickly discharged); (2) the hospital ward group (patients who were admitted to the emergency section and were then hospitalized in a COVID-19 ward); (3) the intensive care unit (ICU) group (patients who required intensive assistance after the admission in the emergency section); (4) the deceased group (patients who had a fatal outcome after admission to the emergency section). Results: We found significant changes for creatinine, azotemia, hematocrit, mean corpuscular hemoglobin concentration, basophils, monocytes, red blood cell distribution width, hemoglobin, hematocrit and red blood cell numbers using ANOVA according to their clinical outcomes, particularly for the deceased group. Also, we found linear correlations of clinical outcomes with eosinophils, hemoglobin, hematocrit, mean corpuscular hemoglobin concentration, lymphocyte, neutrophil, platelet and red blood cell number and red blood cell distribution width. Conclusions: This study discloses an early association between “classical” routine blood biomarkers and the severity of clinical outcomes in Omicron patients.
Related Topics
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.3390/clinpract14030055
- https://www.mdpi.com/2039-7283/14/3/55/pdf?version=1713865940
- OA Status
- gold
- References
- 54
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4395036963
Raw OpenAlex JSON
- OpenAlex ID
-
https://openalex.org/W4395036963Canonical identifier for this work in OpenAlex
- DOI
-
https://doi.org/10.3390/clinpract14030055Digital Object Identifier
- Title
-
Blood Count and Renal Functionality Assessments in the Emergency Section Disclose Morbidity and Mortality in Omicron COVID-19 Patients: A Retrospective StudyWork title
- Type
-
articleOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2024Year of publication
- Publication date
-
2024-04-23Full publication date if available
- Authors
-
Eqrem Rusi, Fiorenza Pennacchia, Wael Abu Ruqa, Maria Antonella Zingaropoli, Patrizia Pasculli, Giuseppina Talarico, Giuseppe Bruno, Christian Barbato, Antonio Minni, Luigi Tarani, Gioacchino Galardo, Francesco Pugliese, Marco Lucarelli, Maria Rosa Ciardi, L. Meucci, Giampiero Ferraguti, Marco FioreList of authors in order
- Landing page
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https://doi.org/10.3390/clinpract14030055Publisher landing page
- PDF URL
-
https://www.mdpi.com/2039-7283/14/3/55/pdf?version=1713865940Direct link to full text PDF
- Open access
-
YesWhether a free full text is available
- OA status
-
goldOpen access status per OpenAlex
- OA URL
-
https://www.mdpi.com/2039-7283/14/3/55/pdf?version=1713865940Direct OA link when available
- Concepts
-
Medicine, Coronavirus disease 2019 (COVID-19), Emergency medicine, Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), 2019-20 coronavirus outbreak, Section (typography), Retrospective cohort study, Intensive care medicine, Internal medicine, Pathology, Disease, Infectious disease (medical specialty), Advertising, Business, OutbreakTop concepts (fields/topics) attached by OpenAlex
- Cited by
-
0Total citation count in OpenAlex
- References (count)
-
54Number of works referenced by this work
- Related works (count)
-
10Other works algorithmically related by OpenAlex
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