MORTALITY AND COVID-19: A SNAPSHOT OF A TERTIARY CARE FACILITY IN PAKISTAN

  1. MA Rana
  2. A Qayyum
  3. M Hashmi
  4. MMU Saif
  5. MF Munir
  6. R Pervaiz
  7. S Iqbal
  8. MM Hafeez

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Abstract

Background: Since SARS CoV-2 infection began in China and has evolved into a pandemic, mortality associated with this illness has been under discussion and hypercoagubility, severe acute respiratory syndrome and septicemia with multiple organ insufficiency have been cursed as potential causes of death in cases infected with the novel coronavirus. We did a retrospective analysis of cases admitted to our highly dependent and intensive care unit, and we tried to identify the leading cause of death in our cases. Methods: This is a single center retrospective study carried out at Bahria International Hospital Lahore over a 3-month period (May 10th to July 10th 2020) in which we analyzed the clinical and biochemical profiles of the COVID-19 patients who died during this period. Results: A total of 108 patients were admitted during this period out of which 11 patients died. 7 of them were men and 4 women. Majority of them had sudden cardiac arrest due to acute coronary syndrome followed by multiorgan dysfunction syndrome and acute respiratory distress syndrome. Conclusion: Acute coronary syndrome due to hypercoagubility was the leading cause of death in our patients.

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  1. Version published to 10.54112/pjicm.v2021i1.3
  2. ScreenIT

    SciScore for 10.1101/2020.08.25.20181792: (What is this?)

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

    Table 1: Rigor

    Institutional Review Board StatementIRB: The study was approved by the ethical committees of hospitals.
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.
    Sex as a biological variablenot detected.

    Table 2: Resources

    Software and Algorithms
    SentencesResources
    We used SPSS (version 21.0) for all analyses.
    SPSS
    suggested: (SPSS, RRID:SCR_002865)

    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.

  3. Version published to 10.1101/2020.08.25.20181792v1 on medRxiv