Characteristics, risk factors and outcomes among the first consecutive 1096 patients diagnosed with COVID-19 in Kuwait

  1. Sulaiman Almazeedi
  2. Sarah Al-Youha
  3. Mohammad H. Jamal
  4. Mohannad Al-Haddad
  5. Ali Al-Muhaini
  6. Fahad Al-Ghimlas
  7. Salman Al-Sabah

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Abstract

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  1. Version published to 10.1016/j.eclinm.2020.100448
  2. ScreenIT

    SciScore for 10.1101/2020.05.09.20096495: (What is this?)

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

    Table 1: Rigor

    Institutional Review Board StatementIRB: Ethical approval for this study was obtained from the Kuwait Ministry of Health Ethical Review Board.
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.
    Sex as a biological variablenot detected.

    Table 2: Resources

    No key resources detected.

    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:
    Limitation: Most of the limitations in our study are due to its retrospective nature, such as potential loss of data due to omissions. In addition, for asymptomatic patients, we did not follow their hospital course and they may have developed symptoms later during their admission. However, based on unpublished reports, we have observed that most patients who were asymptomatic on admission, remained asymptomatic7. Also, as the number of COVID-19 cases escalated, the guidelines for its treatments and discharge/diagnostic criteria slightly evolved over time, which may have implications on our results. At the end of the study, some patients remained hospitalized (10%) and their clinical course is still unclear. Conclusions: This study is, to our knowledge, the first comprehensive study to provide data on the initial 1097 consecutive COVID-19 cases of an entire country, all admitted to a single center, undergoing the same investigations and treatment protocols. We believe it gives a different perspective on the nature and clinical course of this novel disease, compared to other large retrospective cohort studies, as it includes patients with a wide spectrum of disease severity. Future studies, directed at further characterizing risk factors for disease severity and outcomes, particularly predictive scoring systems, are needed.

    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 10.1101/2020.05.09.20096495v1 on medRxiv