Cluster Analysis of Biochemical Markers as Predictor of COVID-19 Severity

Numerous blood biomarkers are altered in COVID-19 patients; however, no early biochemical markers are currently being used in clinical practice to predict COVID-19 severity. COVID-19, the most recent pandemic, is caused by the SRS-CoV-2 coronavirus.  The study was aimed to identify patient groups w...

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Bibliographic Details
Main Authors: Suhayla K. Mohammed, Muzahem Mohialdeen Taha, Ekhlass M. Taha, Massara Najim Abdulla Mohammad
Format: Article
Language:English
Published: University of Baghdad, College of Science for Women 2022-12-01
Series:مجلة بغداد للعلوم
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Online Access:https://bsj.uobaghdad.edu.iq/index.php/BSJ/article/view/7454
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Summary:Numerous blood biomarkers are altered in COVID-19 patients; however, no early biochemical markers are currently being used in clinical practice to predict COVID-19 severity. COVID-19, the most recent pandemic, is caused by the SRS-CoV-2 coronavirus.  The study was aimed to identify patient groups with a high and low risk of developing COVID-19 using a cluster analysis of several biomarkers. 137 women with confirmed SARS CoV-2 RNA testing were collected and analyzed for biochemical profiles. Two-dimensional automated hierarchy clustering of all biomarkers was applied, and patients were sorted into classes. Biochemistry marker variations (Ferritin, lactate dehydrogenase LDH, D-dimer, and C- reactive protein CRP) have split COVID-19 patients into two groups(severe cases and non-severe cases groups). Ferritin, lactate dehydrogenase LDH, D-dimer and CRP were markedly increased in COVID-19 patients in the first group (severe cases). Our findings imply that early measured levels of (Ferritin, lactate dehydrogenase LDH, D-dimer, and C- reactive protein CRP) are linked to a decreased probability of COVID-19 severity. Elevated levels of this biomarker may predict COVID severity development.
ISSN:2078-8665
2411-7986