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. 2022 Sep 12:10:963667.
doi: 10.3389/fpubh.2022.963667. eCollection 2022.

Kidney health in the COVID-19 pandemic: An umbrella review of meta-analyses and systematic reviews

Letian Yang  1 , Jian Li  2 , Wei Wei  1 , Cheng Yi  2 , Yajun Pu  1 , Ling Zhang  1 , Tianlei Cui  1 , Liang Ma  1 , Juqian Zhang  3 , Jay Koyner  4 , Yuliang Zhao  1 , Ping Fu  1
Affiliations

Kidney health in the COVID-19 pandemic: An umbrella review of meta-analyses and systematic reviews

Letian Yang et al. Front Public Health. .

Abstract

Background: This umbrella review aims to consolidate evidence from systematic reviews and meta-analyses investigating the impact of the coronavirus disease-2019 (COVID-19) on kidney health, and the associations between kidney diseases and clinical outcomes in COVID-19 patients.

Methods: Five databases, namely, EMBASE, PubMed, Web of Science, the Cochrane Database of Systematic Reviews and Ovid Medline, were searched for meta-analyses and systematic reviews from January 1, 2020 to June 2, 2022. Two reviewers independently selected reviews, identified reviews for inclusion and extracted data. Disagreements were resolved by group discussions. Two reviewers independently assessed the methodological quality of all included reviews using ROBIS tool. A narrative synthesis was conducted. The characteristics and major findings of the included reviews are presented using tables and forest plots. The included meta-analyses were updated when necessary. The review protocol was prospectively registered in PROSPERO (CRD42021266300).

Results: A total of 103 reviews were identified. Using ROBIS, 30 reviews were rated as low risk of bias. Data from these 30 reviews were included in the narrative synthesis. Ten meta-analyses were updated by incorporating 119 newly available cohort studies. Hospitalized COVID-19 patients had a notable acute kidney injury (AKI) incidence of 27.17%. AKI was significantly associated with mortality (pooled OR: 5.24) and severe conditions in COVID-19 patients (OR: 14.94). The pooled prevalence of CKD in COVID-19 patients was 5.7%. Pre-existing CKD was associated with a higher risk of death (pooled OR: 2.21) and disease severity (pooled OR: 1.87). Kidney transplant recipients were susceptible to SARS-CoV-2 infection (incidence: 23 per 10,000 person-weeks) with a pooled mortality of 18%.

Conclusion: Kidney disease such as CKD or recipients of kidney transplants were at increased risk of contracting COVID-19. Persons with COVID-19 also had a notable AKI incidence. AKI, the need for RRT, pre-existing CKD and a history of kidney transplantation are associated with adverse outcomes in COVID-19.

Systematic review registration: www.crd.york.ac.uk/prospero/display_record.php?ID=CRD42021266300, identifier: CRD42021266300.

Keywords: COVID-19; acute kidney injury; chronic kidney disease; kidney transplant; renal replacement therapy.

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Conflict of interest statement

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Figures

Figure 1
Figure 1
The flowchart of the study search and selection process.
Figure 2
Figure 2
Meta-analysis of incidence of AKI in a random effect model.
Figure 3
Figure 3
The risk factors for AKI in COVID-19 patients. CKD, chronic kidney disease.
Figure 4
Figure 4
Meta-analysis of incidence of urgent RRT in a random effect model.
Figure 5
Figure 5
(A) Meta-analysis of AKI and mortality in a random effect model. (B) Meta-analysis of AKI and disease severity in a random effect model.
Figure 6
Figure 6
Meta-analysis of urgent RRT and mortality in a random effect model.
Figure 7
Figure 7
(A) Meta-analysis of incidence of COVID-19 in the dialysis population in a random effect model. (B) Meta-analysis of prevalence of CKD in COVID-19 patients in a random effect model.
Figure 8
Figure 8
(A) Meta-analysis of CKD and mortality in a random effect model. (B) Meta-analysis of CKD and disease severity in a random effect model.
Figure 9
Figure 9
Meta-analysis of mortality in KTRs with COVID-19 in a random effect model.
See this image and copyright information in PMC

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