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Meta-Analysis
. 2020 Jun 18;24(1):356.
doi: 10.1186/s13054-020-03065-4.

Prevalence and impact of acute renal impairment on COVID-19: a systematic review and meta-analysis

Xianghong Yang  1 , Yiyang Jin  2 , Ranran Li  3 , Zhongheng Zhang  4 , Renhua Sun  5 , Dechang Chen  6   7
Affiliations
Meta-Analysis

Prevalence and impact of acute renal impairment on COVID-19: a systematic review and meta-analysis

Xianghong Yang et al. Crit Care. .

Abstract

Background: The aim of this study is to assess the prevalence of abnormal urine analysis and kidney dysfunction in COVID-19 patients and to determine the association of acute kidney injury (AKI) with the severity and prognosis of COVID-19 patients.

Methods: The electronic database of Embase and PubMed were searched for relevant studies. A meta-analysis of eligible studies that reported the prevalence of abnormal urine analysis and kidney dysfunction in COVID-19 was performed. The incidences of AKI were compared between severe versus non-severe patients and survivors versus non-survivors.

Results: A total of 24 studies involving 4963 confirmed COVID-19 patients were included. The proportions of patients with elevation of sCr and BUN levels were 9.6% (95% CI 5.7-13.5%) and 13.7% (95% CI 5.5-21.9%), respectively. Of all patients, 57.2% (95% CI 40.6-73.8%) had proteinuria, 38.8% (95% CI 26.3-51.3%) had proteinuria +, and 10.6% (95% CI 7.9-13.3%) had proteinuria ++ or +++. The overall incidence of AKI in all COVID-19 patients was 4.5% (95% CI 3.0-6.0%), while the incidence of AKI was 1.3% (95% CI 0.2-2.4%), 2.8% (95% CI 1.4-4.2%), and 36.4% (95% CI 14.6-58.3%) in mild or moderate cases, severe cases, and critical cases, respectively. Meanwhile, the incidence of AKI was 52.9%(95% CI 34.5-71.4%), 0.7% (95% CI - 0.3-1.8%) in non-survivors and survivors, respectively. Continuous renal replacement therapy (CRRT) was required in 5.6% (95% CI 2.6-8.6%) severe patients, 0.1% (95% CI - 0.1-0.2%) non-severe patients and 15.6% (95% CI 10.8-20.5%) non-survivors and 0.4% (95% CI - 0.2-1.0%) survivors, respectively.

Conclusion: The incidence of abnormal urine analysis and kidney dysfunction in COVID-19 was high and AKI is closely associated with the severity and prognosis of COVID-19 patients. Therefore, it is important to increase awareness of kidney dysfunction in COVID-19 patients.

Keywords: 2019-nCoV; Acute kidney injury; Continuous renal replacement therapy; Meta-analysis; Renal impairment; SARS-CoV-2.

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Conflict of interest statement

The authors declare that they have no competing interests.

Figures

Fig. 1
Fig. 1
Flow diagram of the selection process to identify the studies included in the meta-analysis
Fig. 2
Fig. 2
Meta-analysis of the proportion of COVID-19 patients with elevation of serum creatinine and BUN. Heterogeneity is defined based on the calculated I2 index, and random effect models are used to calculate the weights. The forest plots represent proportion of patients with elevation of serum creatinine and BUN (a, b)
Fig. 3
Fig. 3
Meta-analysis of incidence of proteinuria in COVID 19 patients. The forest plots represent the average incidence of proteinuria (a), proteinuria + (b), and proteinuria ++/+++ (c) in COVID-19 patients. Heterogeneity is defined based on the calculated I2 index. Based on the heterogeneity, random effect models are used to calculate the weights in a and b, and the fixed effect model is used to calculate weights in c
Fig. 4
Fig. 4
a Forest plot of average AKI incidence in all COVID-19 patients. b Forest plots of AKI log risk ratio between severe and non-severe patients. c Forest plots of AKI log risk ratio between survival and non-survival cases. Heterogeneity is defined based on the calculated I2 index, and random effect models are used to calculate the weights
Fig. 5
Fig. 5
a Forest plot of average AKI incidence in critical COVID-19 cases. b Forest plot of average AKI incidence in severe COVID-19 cases. c Forest plot of average AKI incidence in mild/moderate COVID-19 cases. Heterogeneity is defined based on the I2 index calculated. A random effect model is used to pool the average AKI incidence in critical patients, and fixed effect models are used to pool the data of AKI incidence in severe and mild/moderate cases
Fig. 6
Fig. 6
Meta-analysis of relative risk of CRRT application on severe and non-survival cases compared with non-severe and survival cases. a The forest plot represents the relative risk of CRRT application on severe patients compared with non-severe patients. b The forest plot represents the relative risk of CRRT application on non-survival cases compared with survival cases. Heterogeneity is defined based on the calculated I2 index, and fixed effect models are used to calculate the weights
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