Acute kidney injury is associated with severe and fatal outcomes in patients with Coronavirus disease 2019 (COVID-19) infection: a systematic review and meta-analysis of observational studies

  1. Mohammad Parohan
  2. Sajad Yaghoubi
  3. Mahmoud Djalali
  4. Asal Seraji
  5. Mohammad Hassan Javanbakht
  6. Zahra Mousavi

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Abstract

Coronavirus disease 2019 (COVID-19) is a pandemic impacting 213 countries and territories with more than 17,918,582 cases worldwide. Kidney dysfunction has been reported to occur in severe and death cases. This meta-analysis was done to summarize available studies on the association between acute kidney injury and severity of COVID-19 infection. Online databases including Web of Science, PubMed/Medline, Cochrane Library, Scopus and Google Scholar were searched to detect relevant articles up to 1 July 2020, using relevant keywords. To pool data, a random- or fixed-effects model was used based on the heterogeneity between studies. In total, 50 studies with 8,180 COVID-19 confirmed cases (severe cases=1,823 and death cases=775), were included in this meta-analysis. Higher serum levels of creatinine (weighted mean difference (WMD) for disease severity=5.47 μmol/L, 95% CI=2.89 to 8.05, P<0.001 and WMD for mortality=18.32 μmol/L, 95% CI=12.88 to 23.75, P<0.001), blood urea nitrogen (BUN) (WMD for disease severity=1.10 mmol/L, 95% CI=0.67 to 1.54, P<0.001 and WMD for mortality=3.56 mmol/L, 95% CI=2.65 to 4.48, P<0.001) and lower levels of estimated glomerular filtration rate (eGFR) (WMD for disease severity=-15.34 mL/min/1.73 m 2 , 95% CI=-18.46 to -12.22, P<0.001 and WMD for mortality=-22.74 mL/min/1.73 m 2 , 95% CI=-27.18 to -18.31, P<0.001) were associated with a significant increase in the severity and mortality of COVID-19 infection. Acute kidney injury, as assessed by kidney biomarkers (serum creatinine, BUN and eGFR), was associated with severe outcome and death from COVID-19 infection.

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  1. ScreenIT

    SciScore for 10.1101/2020.08.27.20183632: (What is this?)

    Please note, not all rigor criteria are appropriate for all manuscripts.

    Table 1: Rigor

    Institutional Review Board Statementnot detected.
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.
    Sex as a biological variablenot detected.

    Table 2: Resources

    Software and Algorithms
    SentencesResources
    Search strategy: We conducted a systematic search using the online databases of Web of Science, PubMed/Medline, Cochrane Library, Scopus and Google Scholar for relevant articles up to 1 July 2020.
    Cochrane Library
    suggested: (Cochrane Library, RRID:SCR_013000)
    Google Scholar
    suggested: (Google Scholar, RRID:SCR_008878)
    The following medical subject headings (MeSH) and non-MeSH terms were used: (“Novel Coronavirus” OR “2019‐nCoV” OR “Coronavirus disease 2019” OR “COVID-19” OR “Severe acute respiratory syndrome Coronavirus 2” OR “SARS-CoV-2”) AND (“estimated Glomerular filtration rate” OR “eGFR” OR “Creatinine clearance” OR “Blood Urea Nitrogen” OR “BUN” OR “Creatinine” OR “Kidney diseases” OR “Acute Kidney injury”).
    MeSH
    suggested: (MeSH, RRID:SCR_004750)
    The search results were downloaded into an EndNote library (version X8, Thomson Reuters, Philadelphia, USA) and titles/abstracts assessed for eligibility.
    EndNote
    suggested: (EndNote, RRID:SCR_014001)
    Heterogeneity between studies was assessed using the Cochrane Q test and I2 statistics 58.
    Cochrane Q
    suggested: None

    Results from OddPub: We did not detect open data. We also did not detect open code. Researchers are encouraged to share open data when possible (see Nature blog).

    Results from LimitationRecognizer: An explicit section about the limitations of the techniques employed in this study was not found. We encourage authors to address study limitations.

    Results from TrialIdentifier: No clinical trial numbers were referenced.

    Results from Barzooka: We did not find any issues relating to the usage of bar graphs.

    Results from JetFighter: We did not find any issues relating to colormaps.

    Results from rtransparent:
    • Thank you for including a conflict of interest statement. Authors are encouraged to include this statement when submitting to a journal.
    • Thank you for including a funding statement. Authors are encouraged to include this statement when submitting to a journal.
    • No protocol registration statement was detected.

    About SciScore

    SciScore is an automated tool that is designed to assist expert reviewers by finding and presenting formulaic information scattered throughout a paper in a standard, easy to digest format. SciScore checks for the presence and correctness of RRIDs (research resource identifiers), and for rigor criteria such as sex and investigator blinding. For details on the theoretical underpinning of rigor criteria and the tools shown here, including references cited, please follow this link.

  2. Version published to 10.1101/2020.08.27.20183632v1 on medRxiv