مرکز اطلاعات علمی Scientific Information Database (SID) - Trusted Source for Research and Academic Resources

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مرکز اطلاعات علمی Scientific Information Database (SID) - Trusted Source for Research and Academic Resources

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Information Journal Paper

Title

The Association Between Laboratory Biomarkers and Clinical Features in COVID-19 Pneumonia: A Potential Tool for Predicting Disease Prognosis and Severity

Pages

  73-82

Abstract

 Background: The COVID-19 pandemic has rapidly spread and remained poorly understood by clinicians. The present work aimed to study the association between Laboratory biomarkers, prognosis, and disease severity. Methods: This is a single-center cohort study. We included young patients admitted at Razi Hospital, Ghaemshar City, Iran, from April 2020 to June 2020, whose diseases were confirmed with reverse transcription real time-PCR (rRT-PCR) test. Laboratory biomarkers were analyzed on the same day of inpatient service and after five days of hospitalization. The patients’ results and the outcomes were compared with those of the control group. Results: In the present study, 70 patients were investigated,53 were discharged, and 17 died. A significant correlation was observed between patients and healthy subjects in some Laboratory biomarkers: C-reactive protein (CRP), lactate dehydrogenase (LDH), total protein level, albumin level, and absolute lymphocyte count. Furthermore, CRP, LDH, total protein, albumin, absolute lymphocyte count, 25-OH vitamin D, interleukin (IL)-6, ferritin, and D-dimer levels in patients with different outcomes had significant correlations. High CRP, LDH, IL-6, ferritin, and D-dimer were predictive of mortality (area under the curve >0. 70), as were low absolute lymphocyte count and 25-OH vitamin D. After adjusting age, CRP, albumin, WBC, D-dimer, LDH, and 25 OH-vitamin D, the final model of multiple binary logistic regressions with IL-6 and ferritin had high accuracy for the prediction of fatal outcome. Conclusion: This finding would facilitate the early stratification of hospitalized patients with COVID-19 and help make clinical decisions.

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