The dynamics of inflammatory markers in coronavirus disease-2019 (COVID-19) patients: A systematic review and meta-analysis

Background: Coronavirus disease-2019 (COVID-19) is a global pandemic and high mortality rate among severe or critical COVID-19 is linked with SARS-CoV-2 infection-induced hyperinflammation of the innate and adaptive immune systems and the resulting cytokine storm. This paper attempts to conduct a sy...

Full description

Saved in:
Bibliographic Details
Main Authors: Roshan Kumar Mahat (Author), Suchismita Panda (Author), Vedika Rathore (Author), Sharmistha Swain (Author), Lalendra Yadav (Author), Sumesh Prasad Sah (Author)
Format: Book
Published: Elsevier, 2021-07-01T00:00:00Z.
Subjects:
Online Access:Connect to this object online.
Tags: Add Tag
No Tags, Be the first to tag this record!

MARC

LEADER 00000 am a22000003u 4500
001 doaj_cfdbee34c17e43f9b704f36244cb0bfe
042 |a dc 
100 1 0 |a Roshan Kumar Mahat  |e author 
700 1 0 |a Suchismita Panda  |e author 
700 1 0 |a Vedika Rathore  |e author 
700 1 0 |a Sharmistha Swain  |e author 
700 1 0 |a Lalendra Yadav  |e author 
700 1 0 |a Sumesh Prasad Sah  |e author 
245 0 0 |a The dynamics of inflammatory markers in coronavirus disease-2019 (COVID-19) patients: A systematic review and meta-analysis 
260 |b Elsevier,   |c 2021-07-01T00:00:00Z. 
500 |a 2213-3984 
500 |a 10.1016/j.cegh.2021.100727 
520 |a Background: Coronavirus disease-2019 (COVID-19) is a global pandemic and high mortality rate among severe or critical COVID-19 is linked with SARS-CoV-2 infection-induced hyperinflammation of the innate and adaptive immune systems and the resulting cytokine storm. This paper attempts to conduct a systematic review and meta-analysis of published articles, to evaluate the association of inflammatory parameters with the severity and mortality in COVID-19 patients. Methods: A comprehensive systematic literature search of medical electronic databases including Pubmed/Medline, Europe PMC, and Google Scholar was performed for relevant data published from January 1, 2020 to June 26, 2020. Observational studies reporting clear extractable data on inflammatory parameters in laboratory-confirmed COVID-19 patients were included. Screening of articles, data extraction and quality assessment were carried out by two authors independently. Standardized mean difference (SMD)/mean difference (MD/WMD) and 95% confidence intervals (CIs) were calculated using random or fixed-effects models. Results: A total of 83 studies were included in the meta-analysis. Of which, 54 studies were grouped by severity, 25 studies were grouped by mortality, and 04 studies were grouped by both severity and mortality. Random effect model results demonstrated that patients with severe COVID-19 group had significantly higher levels of C-reactive protein (CRP), erythrocyte sedimentation rate (ESR), procalcitonin (PCT), interleukin-6 (IL-6), interleukin-10 (IL-10), interleukin-2R (IL-2R), serum amyloid A (SAA) and neutrophil-to-lymphocyte ratio (NLR) compared to those in the non-severe group. Similarly, the fixed-effect model revealed significant higher ferritin level in the severe group when compared with the non-severe group. Furthermore, the random effect model results demonstrated that the non-survivor group had significantly higher levels of CRP, PCT, IL-6, ferritin, and NLR when compared with the survivor group. Conclusion: In conclusion, the measurement of these inflammatory parameters could help the physicians to rapidly identify severe COVID-19 patients, hence facilitating the early initiation of effective treatment. Prospero registration number: CRD42020193169. 
546 |a EN 
690 |a COVID-19 
690 |a SARS-CoV-2 
690 |a Coronavirus infections 
690 |a Cytokine release syndrome 
690 |a Public aspects of medicine 
690 |a RA1-1270 
655 7 |a article  |2 local 
786 0 |n Clinical Epidemiology and Global Health, Vol 11, Iss , Pp 100727- (2021) 
787 0 |n http://www.sciencedirect.com/science/article/pii/S2213398421000312 
787 0 |n https://doaj.org/toc/2213-3984 
856 4 1 |u https://doaj.org/article/cfdbee34c17e43f9b704f36244cb0bfe  |z Connect to this object online.