Document Type : Review
Authors
1 School of Medicine, Mashhad University of Medical Sciences, Mashhad, Iran.
2 Antimicrobial resistance research center, Buali research Institute, Department of Microbiology and Virology, Faculty of Medicine, Mashhad University of Medical Sciences, Mashhad, Iran.
3 Rheumatic Diseases Research Center, School of Medicine, Mashhad University of Medical Sciences, Mashhad, Iran. Departments of Rheumatology, School of Medicine, Mashhad University of Medical Sciences, Mashhad, Iran.
4 Department of Internal Medicine, School of Medicine, Mashhad University of Medical Sciences, Mashhad, Iran
Abstract
The coronavirus disease 2019 (COVID-19), which has spread to many countries, is so severe that it progresses rapidly to acute respiratory failure. Therefore, in our paper, we aimed to describe and evaluate the most practical laboratory pro-inflammatory factors to predict the course of severe COVID-19 cases.
Given the physiopathology of COVID-19 and the consequent immune system hyperactivity, we started to investigate the background pathology of these occurrences aiming to find the prognostic laboratory factors in COVID-19 cases. All reviews focused on the potential cellular and molecular mechanisms causing the cytokine storm in viral diseases, and several studies approved applicable laboratory parameters for COVID-19 patients. Based on our data, increased CRP level, LDH, serum ferritin, creatine kinase (CK), higher D-dimer and FDP levels, IL-6, cardiac troponin I and longer PT can be potential markers for predicting the course of infection; particularly, D-dimer, which was elevated to five times the original count in severe cases. Apart from that, the severe cases showed lymphopenia, neutrophilia, thrombocytopenia, and prolonged PTT. However, there was contradictory evidence about AST, ALT, BUN, and serum creatinine.
The major cause of COVID-19 in critical patients was a cytokine storm; therefore, prognostic factors in the cytokine storm can also predict the prognosis of COVID-19. Thus, severe cases can be solved by early detection of these laboratory parameters.
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