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Risk factors for acute kidney injury in COVID-19 patients: an updated systematic review and meta-analysis.


ABSTRACT: Objectives: Acute kidney injury (AKI) is associated with increased mortality among coronavirus disease 2019 (COVID-19) patients. This meta-analysis aimed to identify risk factors for the development of AKI in patients with COVID-19.Methods: A systematic literature search was conducted in PubMed and EMBASE from 1 December 2019 to 1 January 2023. Due to significant study heterogeneity, meta-analyses were conducted using random-effects models. Meta-regression and sensitivity analysis were also performed.Results: A total of 153,600 COVID-19 patients from 39 studies were included, and 28,003 patients developed AKI. By meta-analysis, we discovered that age, male sex, obesity, black race, invasive ventilation, and the use of diuretics, steroids and vasopressors, in addition to comorbidities such as hypertension, congestive heart failure, chronic kidney disease, acute respiratory distress syndrome, and diabetes, were significant risk factors for COVID-19-associated AKI.Conclusions: Early detection of these risk factors is essential to reduce the incidence of AKI and improve the prognosis of COVID-19 patients.

SUBMITTER: Zhang J 

PROVIDER: S-EPMC10081062 | biostudies-literature | 2023 Dec

REPOSITORIES: biostudies-literature

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Risk factors for acute kidney injury in COVID-19 patients: an updated systematic review and meta-analysis.

Zhang Jialing J   Pang Qi Q   Zhou Ting T   Meng Jiali J   Dong Xingtong X   Wang Zhe Z   Zhang Aihua A  

Renal failure 20231201 1


<b>Objectives:</b> Acute kidney injury (AKI) is associated with increased mortality among coronavirus disease 2019 (COVID-19) patients. This meta-analysis aimed to identify risk factors for the development of AKI in patients with COVID-19.<b>Methods:</b> A systematic literature search was conducted in PubMed and EMBASE from 1 December 2019 to 1 January 2023. Due to significant study heterogeneity, meta-analyses were conducted using random-effects models. Meta-regression and sensitivity analysis  ...[more]

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