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Inflammatory and hematologic markers as predictors of severe outcomes in COVID-19 infection: A systematic review and meta-analysis

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AMERICAN JOURNAL OF EMERGENCY MEDICINE
卷 41, 期 -, 页码 110-119

出版社

W B SAUNDERS CO-ELSEVIER INC
DOI: 10.1016/j.ajem.2020.12.076

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COVID-19; SARS-CoV-2; Coronavirus; Laboratory; Biomarker

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The meta-analysis suggests that COVID-19 patients with elevated procalcitonin, CRP, D-dimer, and LDH levels, as well as decreased albumin levels, may be more likely to develop severe outcomes.
Background: Laboratory testing is commonly performed in patients with COVID-19. Each of the laboratory parameters has potential value for risk stratification and prediction of COVID-19 outcomes. This systematic review and meta-analysis aimed to evaluate the difference between these parameters in severe and nonsevere disease and to provide the optimal cutoff value for predicting severe disease. Method: We performed a systematic literature search through electronic databases. The variables of interest were serum procalcitonin, albumin, C-reactive protein (CRP), D-dirner, and lactate dehydrogenase (LDH) levels in each group of severity outcomes from COVID-19. Results: There were a total of 4848 patients from 23 studies. Our meta-analysis suggest that patients with severe COVID-19 infections have higher procalcitonin, (mean difference 0.07; 95% CI 0.05-0.10; p < 0.00001), CRP (mean difference 36.88; 95% CI 29.10-44.65; p < 0.00001), D-Dimer (mean difference 0.43; 95% CI 0.31-0.56; p < 0.00001), and LDH (mean difference 102.79; 95% a 79.10-126.49; p < 0.00001) but lower levels of albumin ( mean difference -458; 95% CI -5.76 to -339; p < 0.00001) than those with nonsevere COVID-19 infections. The cutoff values for the parameters were 0.065 ng/mL for procalcitonin, 38.85 g/L for albumin, 33.55 mg/L for CRP, 0.635 mu/L for D-dimer, and 263.5 U/L for LDH, each with high sensitivity and specificity. Conclusion: This meta-analysis suggests elevated procalcitonin, CRP, D-dimer, and LDH and decreased albumin can be used for predicting severe outcomes in COVID-19. (C) 2020 Elsevier Inc. All rights reserved.

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