Effects of underlying morbidities on the occurrence of deaths in COVID-19 patients: A systematic review and meta-analysis

  1. Md Mostaured Ali Khan
  2. Md Nuruzzaman Khan
  3. Md Golam Mustagir
  4. Juwel Rana
  5. Md Saiful Islam
  6. Md Iqbal Kabir

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Abstract

No abstract available

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  1. Version published to 10.7189/jogh.10.020503
  2. ScreenIT

    SciScore for 10.1101/2020.05.08.20095968: (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 variableExclusion criteria: Studies excluded if COVID-19 was reported among pregnant women or children (aged <18 years) and written in languages other than English.

    Table 2: Resources

    Software and Algorithms
    SentencesResources
    Search strategy: Four databases: Medline, Web of Science, Scopus, and CINAHL were searched, concluded on May 01, 2020, using pre-specified search strategies for each database.
    Medline
    suggested: (MEDLINE, RRID:SCR_002185)
    Additional searches were conducted using the reference list of the selected studies, relevant journal websites, and renowned pre-print servers (medRxiv, bioRxiv, SSRN).
    bioRxiv
    suggested: (bioRxiv, RRID:SCR_003933)
    Stata software version 15.1 (StataCorp.
    Stata
    suggested: (Stata, RRID:SCR_012763)
    StataCorp
    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:
    Strengths and limitations: This study has several strengths and limitations that should be reported. To our knowledge, this is the first of its kind that summarizes all morbidities among COVID-19 patients that lead to death. Moreover, morbidities reported among COVID-19 patients were classified into board groups based on their characteristics, and the likelihood of death was estimated separately for each group. This evidence informs healthcare providers about the risk of death among COVID-19 patients with different groups of pre-existing morbidities. Thus, they will be able to take precautionary measures early targeting to prevent deaths. However, this study reported the odds of death for COVID-19 patients with one pre-existing morbidity only. Many COVID-19 patients may have multi-morbidities (COVID-19 with pre-existing two or more morbidities) and a higher risk of death. However, the studies included in this review considered each morbidity separately; for instance, if COVID-19 patients had both hypertension and diabetes, they were included in both groups. None of the included studies considered COVID-19 with two or more morbidities together; therefore, we failed to provide the likelihood of deaths for COVID-19 patients with two or more pre-existing morbidities. Moreover, the likelihoods presented in this study were mostly unadjusted (31 of the 36 articles included) calculated from the extracted raw data. This may overestimate or underestimate the actual likelihood of deaths...

    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 10.1101/2020.05.08.20095968 on medRxiv