Liver Function in Novel Coronavirus Disease (COVID-19): A Systematic Review and Meta-Analysis

  1. Mohammad Zahedi
  2. Mohammad Yousefi
  3. Mahdi Abounoori
  4. Mohammad Malekan
  5. Fatemeh Tajik
  6. Keyvan Heydari
  7. Parham Mortazavi
  8. Monireh Ghazaeian
  9. Fateme Sheydaee
  10. Amirreza Nasirzadeh
  11. Reza Alizadeh-Navaei

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Abstract

Introduction:The outbreak of new coronavirus has become a global public health challenge. Given a consequential liver function, and the high risk of death coming from liver disorders, the assessment of Novel Coronavirus Disease on liver function is importance. Hence, we carried out this meta-analysis to heightening insight into the occult features of COVID 19, which is likely to affect liver function. Method:This study was performed using databases of Web of Science, Scopus, and PubMed. We considered English cross-sectional and case-series papers, which reported available findings on the association between liver injury and COVID-19 infection. We used the STATA v.11 and random effect model for data analysis. Result:In this present meta-analysis, 52 papers, including 8,463 COVID-19 patients, were studied. The prevalence of increased liver enzymes among the patients, including Alanine aminotransferase, Aspartate aminotransferase, were 30% and 21% in non-severe patients, respectively, which were 38% and 48% in severe patients. The prevalence of increasing C-reactive protein, Lactate dehydrogenase, D-dimer, and Bilirubin were 55%, 39%, 28%, and 10% in non-severe patients respectively, which were 78%, 75%, 79% and 17% in sever patients.The prevalence of liver toxicity as a complication of COVID-19 was 20%.Also patients who have severe condition are 5.54, 4.22, 4.96, 4.13 and 4.34 times more likely to have elevated CRP, ALT, AST, LDH, D-dimer enzymes retrospectively. Conclusion:Elevation of some liver markers were higher in patients with severe COVID-19 infection. All to gather, we assumed that abnormal liver markers could act as a prognostic factor for a better survey of COVID-19.

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  1. ScreenIT

    SciScore for 10.1101/2020.05.20.20108357: (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 engines and databases, including Web of Science, Scopus, and PubMed without any time limitation for publications up to April 19, 2020.
    PubMed
    suggested: (PubMed, RRID:SCR_004846)
    As a manual search, the list of imported references, a list of related reviews, and the results of Google Scholar have been investigated.
    Google Scholar
    suggested: (Google Scholar, RRID:SCR_008878)
    Study Selection: Duplicated papers were deleted using EndNote software (version X8, Thomson Reuters, Philadelphia, USA).
    EndNote
    suggested: (EndNote, RRID:SCR_014001)
    Statistical Analysis: Statistical analysis was performed using STATA v.
    STATA
    suggested: (Stata, RRID:SCR_012763)

    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. All of the studies have been conducted in China, whereas covid19 is pandemic now. Interpretation of our meta-analysis findings might be limited by the small sample size. limitations on the information provided in studies constrained subgroup analysis.

    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 10.1101/2020.05.20.20108357v1 on medRxiv