Liver injury is associated with severe coronavirus disease 2019 (COVID‐19) infection: A systematic review and meta‐analysis of retrospective studies

  1. Mohammad Parohan
  2. Sajad Yaghoubi
  3. Asal Seraji

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Abstract

The coronavirus disease 2019 (COVID‐19) outbreak is a major threat to human beings. Lung injury has been reported as the major outcome of COVID‐19 infection. However, liver damage has also been considered to occur in severe cases. The current meta‐analysis of retrospective studies was carried out to summarize available findings on the association between liver injury and severity of COVID‐19 infection. Online databases including PubMed, Scopus, Web of Science, and Cochrane Library were searched to detect relevant publications up to 1 April 2020, using relevant keywords. To pool data, a fixed‐ or random‐effects model was used depending on the heterogeneity between studies. Furthermore, publication bias test and sensitivity analysis were also applied. In total, 20 retrospective studies with 3428 COVID‐19 infected patients (severe cases, n  = 1455; mild cases, n  = 1973), were included in this meta‐analysis. Higher serum levels of aspartate aminotransferase (weighted mean difference, 8.84 U/L; 95% confidence interval [CI] 5.97 to 11.71; P  < 0.001), alanine aminotransferase (weighted mean difference, 7.35 U/L; 95% CI, 4.77 to 9.93; P  < 0.001), total bilirubin (weighted mean difference, 2.30 mmol/L; 95% CI, 1.24 to 3.36; P  < 0.001), and lower serum levels of albumin (weighted mean difference, −4.24 g/L; 95% CI, −6.20 to −2.28; P  < 0.001) were associated with a significant increase in the severity of COVID‐19 infection. The incidence of liver injury, as assessed by serum analysis (aspartate aminotransferase, alanine aminotransferase, total bilirubin, and albumin levels), seems to be higher in patients with severe COVID‐19 infection.

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  1. Version published to 10.1111/hepr.13510
  2. ScreenIT

    SciScore for 10.1101/2020.04.09.20056242: (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 literature search using the online databases of PubMed, Scopus, Web of Science and Cochrane Library for relevant publications up to 1 April 2020.
    PubMed
    suggested: (PubMed, RRID:SCR_004846)
    Cochrane Library
    suggested: (Cochrane Library, RRID:SCR_013000)
    The following medical subject headings (MeSH) and non-MeSH keywords were used in our search strategy: (“COVID-19” OR “severe acute respiratory syndrome coronavirus 2” OR “SARS-CoV-2” OR “novel coronavirus” OR “2019-nCoV”) AND (“Alanine Transaminase” OR “Alanine aminotransferase” OR “SGPT” OR “Aspartate Aminotransferases” OR “SGOT” OR “Bilirubin” OR “Serum Albumin” OR “Liver”).
    MeSH
    suggested: (MeSH, RRID:SCR_004750)
    To facilitate the screening process of studies from online databases, all search results were downloaded into an EndNote library (version X8, Thomson Reuters, Philadelphia, USA).
    EndNote
    suggested: (EndNote, RRID:SCR_014001)
    The heterogeneity between studies was evaluated using the Cochrane Q test 30.
    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: We detected the following sentences addressing limitations in the study:
    The present study has some limitations. First, interpretation of our meta-analysis findings might be limited by the small sample size. Second, there is a lack of reports that liver failure occurs in COVID-19 patients with chronic liver diseases and our meta-analysis did not include data such as chronic hepatitis B or C.

    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.

  3. Version published to 10.1101/2020.04.09.20056242v1 on medRxiv