Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
Review
. 2022 Aug 16;7(8):186.
doi: 10.3390/tropicalmed7080186.

C-Reactive Protein-to-Albumin Ratio and Clinical Outcomes in COVID-19 Patients: A Systematic Review and Meta-Analysis

Hernán J Zavalaga-Zegarra  1 , Juan J Palomino-Gutierrez  1 , Juan R Ulloque-Badaracco  1   2 , Melany D Mosquera-Rojas  1   2 , Enrique A Hernandez-Bustamante  3   4 , Esteban A Alarcon-Braga  1   2 , Vicente A Benites-Zapata  5 , Percy Herrera-Añazco  6   7 , Adrian V Hernandez  8   9
Affiliations
Review

C-Reactive Protein-to-Albumin Ratio and Clinical Outcomes in COVID-19 Patients: A Systematic Review and Meta-Analysis

Hernán J Zavalaga-Zegarra et al. Trop Med Infect Dis. .

Abstract

C-reactive protein-to-albumin ratio (CAR) is an independent risk factor in cardiovascular, cerebrovascular, and infectious diseases. Through this study, we investigated the CAR values with respect to the severity and mortality of COVID-19 patients. We performed a systematic review and meta-analysis to retrieve studies that evaluated CAR values upon hospital admission in relation to the severity or mortality of COVID-19 patients. We adopted a random-effect model to calculate the pooled mean difference (MD) and their 95% confidence intervals (CI). Quality assessment was appraised using a Newcastle−Ottawa scale and publication bias was assessed using the Begg-test and funnel plot. We equally performed a subgroup analysis using study location and a sensitivity analysis only with studies with low risk of bias. We analyzed 32 studies (n = 12445). Severe COVID-19 patients had higher on-admission CAR values than non-severe COVID-19 patients (MD: 1.69; 95% CI: 1.35−2.03; p < 0.001; I2 = 89%). Non-survivor patients with COVID-19 had higher CAR values than survivor patients (MD: 2.59; 95% CI: 1.95−3.23; p < 0.001; I2 = 92%). In sensitivity analysis, the relationship remained with a decreasing of heterogeneity for severity (MD: 1.22; 95% CI: 1.03−1.40; p < 0.001; I2 = 13%) and for mortality (MD: 2.99; 95% CI: 2.47−3.51; p < 0.001; I2 = 0%). High CAR values were found in COVID-19 patients who developed severe disease or died.

Keywords: C-reactive protein; COVID-19; albumin; meta-analysis.

PubMed Disclaimer

Conflict of interest statement

The authors declare no conflict of interest.

Figures

Figure 1
Figure 1
PRISMA Flow Diagram.
Figure 2
Figure 2
(A) CAR values in severe vs. non-severe COVID-19 patients. [19,22,23,24,25,28,33,34,35,36,37,38,39,40,41,47,48,49,50] (B) Subgroup analysis according to country of origin between severe vs. non-severe COVID-19 patients. [19,22,23,24,25,28,33,34,35,36,37,38,39,40,41,47,48,49,50]. (C) Sensitivity analysis according to the risk of bias between severe vs. non-severe COVID-19 patients [19,22,23,24,25,28,35,38].
Figure 2
Figure 2
(A) CAR values in severe vs. non-severe COVID-19 patients. [19,22,23,24,25,28,33,34,35,36,37,38,39,40,41,47,48,49,50] (B) Subgroup analysis according to country of origin between severe vs. non-severe COVID-19 patients. [19,22,23,24,25,28,33,34,35,36,37,38,39,40,41,47,48,49,50]. (C) Sensitivity analysis according to the risk of bias between severe vs. non-severe COVID-19 patients [19,22,23,24,25,28,35,38].
Figure 3
Figure 3
(A) CAR values in non-survivor vs. survivor COVID-19 patients [20,21,23,26,27,29,30,31,32,34,43,44,45,46,47,50]. (B) Subgroup analysis according to country of origin between non-survivor vs. survivor COVID-19 patients. [20,21,23,26,27,29,30,31,32,34,43,44,45,46,47,50] (C) Sensitivity analysis according to the risk of bias between non-survivor vs. survivor COVID-19 patients [21,23,27,30,31].
Figure 3
Figure 3
(A) CAR values in non-survivor vs. survivor COVID-19 patients [20,21,23,26,27,29,30,31,32,34,43,44,45,46,47,50]. (B) Subgroup analysis according to country of origin between non-survivor vs. survivor COVID-19 patients. [20,21,23,26,27,29,30,31,32,34,43,44,45,46,47,50] (C) Sensitivity analysis according to the risk of bias between non-survivor vs. survivor COVID-19 patients [21,23,27,30,31].
See this image and copyright information in PMC

Similar articles

See all similar articles

Cited by

See all "Cited by" articles

References

    1. Bonilla-Aldana D.K., Quintero-Rada K., Montoya-Posada J.P., Ramírez-Ocampo S., Paniz-Mondolfi A., Rabaan A.A., Sah R., Rodríguez-Morales A.J. SARS-CoV, MERS-CoV and Now the 2019-Novel CoV: Have We Investigated Enough about Coronaviruses?—A Bibliometric Analysis. Travel Med. Infect. Dis. 2020;33:101566. doi: 10.1016/j.tmaid.2020.101566. - DOI - PMC - PubMed
    1. WHO Coronavirus (COVID-19) Dashboard | WHO Coronavirus (COVID-19) Dashboard with Vaccination Data. [(accessed on 13 November 2021)]; Available online: https://covid19.who.int/
    1. Ray D., Salvatore M., Bhattacharyya R., Wang L., Du J., Mohammed S., Purkayastha S., Halder A., Rix A., Barker D., et al. Predictions, Role of Interventions and Effects of a Historic National Lockdown in India’s Response to the COVID-19 Pandemic: Data Science Call to Arms. Harv. Data Sci. Rev. 2020 doi: 10.1162/99608F92.60E08ED5. - DOI - PMC - PubMed
    1. Li L.Q., Huang T., Wang Y.Q., Wang Z.P., Liang Y., Huang T.B., Zhang H.Y., Sun W., Wang Y. COVID-19 Patients’ Clinical Characteristics, Discharge Rate, and Fatality Rate of Meta-Analysis. J. Med. Virol. 2020;92:577–583. doi: 10.1002/jmv.25757. - DOI - PMC - PubMed
    1. Tian W., Jiang W., Yao J., Nicholson C.J., Li R.H., Sigurslid H.H., Wooster L., Rotter J.I., Guo X., Malhotra R. Predictors of Mortality in Hospitalized COVID-19 Patients: A Systematic Review and Meta-analysis. J. Med. Virol. 2020;92:1875–1883. doi: 10.1002/jmv.26050. - DOI - PMC - PubMed