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

Roshan Kumar Mahat; Suchismita Panda; Vedika Rathore; Sharmistha Swain; Lalendra Yadav; Sumesh Prasad Sah

doi:10.1016/j.cegh.2021.100727

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

Clin Epidemiol Glob Health. 2021 Jul-Sep:11:100727. doi: 10.1016/j.cegh.2021.100727. Epub 2021 Mar 20.

Authors

Roshan Kumar Mahat¹, Suchismita Panda¹, Vedika Rathore², Sharmistha Swain¹, Lalendra Yadav³, Sumesh Prasad Sah⁴

Affiliations

¹ Department of Biochemistry, Pandit Raghunath Murmu Medical College and Hospital, Baripada, Mayurbhanj, Odisha, 757107, India.
² Department of Biochemistry, Shyam Shah Medical College, Rewa, Madhya Pradesh, 486001, India.
³ Department of Pharmacology, Teerthanker Mahaveer Medical College and Research Center, Moradabad, Uttar Pradesh, 244001, India.
⁴ Department of Biochemistry, Muzaffarnagar Medical College, Muzaffarnagar, Uttar Pradesh, 251203, India.

Abstract

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.

Keywords: COVID-19; Coronavirus infections; Cytokine release syndrome; SARS-CoV-2.

Publication types

Review