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Updated: Sep 21, 2025

Dynamic Monitoring of Seroconversion using a Multianalyte Immunobead Assay for Covid-19
Published on: February 16, 2022
Laboratory biomarker predictors for disease progression and outcome among Egyptian COVID-19 patients
Lamiaa A Fathalla1, Lamyaa M Kamal2, Omina Salaheldin3
1Department of Clinical Pathology, 68804National Cancer Institute, Cairo University, Cairo, Egypt.
Abstract:
The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic resulted in more than five hundred million infected cases worldwide. The current study aimed to screen the correlation of different laboratory findings with disease severity and clinical outcomes of coronavirus disease (COVID-19) among Egyptian patients to obtain prognostic indicators of disease severity and outcome.A total of 112 laboratory-confirmed COVID-19 patients were examined. According to the severity of the disease, these patients were divided into three main groups: mild, moderate and severe cases. In addition, clinical characteristics and laboratory findings, including Hb, platelet count, white blood cell count, lymphocyte percentage, neutrophil percentage, neutrophil lymphocyte ratio (NLR), D-dimer, highly sensitive C-reactive protein (HS-CRP), alanine aminotransferase (ALT), lactate dehydrogenase (LDH) and creatinine, were measured.The presence of hypertension and/or diabetes was found to be a significant risk factor for disease severity and poor outcome. Increased respiratory rate, levels of SpO2, HS-CRP, D-dimer, NLR, ALT, LDH, lymphopenia and neutrophilia, as well as changes in chest computed tomography (CT), were associated with increased disease severity and fatal consequences. Highly sensitive C-reactive protein, D-dimer, NLR and LDH constituted excellent predictors for both disease severity and death.Laboratory biomarkers, such as HS-CRP, D-dimer, NLR and LDH, are excellent predictors for both disease severity and death. They can predict mortality in patients at the time of admission secondary to SARS-CoV-2 infection and can help physicians identify high-risk patients before clinical deterioration.
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