The Clinical Utility of Serial Procalcitonin and Procalcitonin Clearance in Predicting the ‎Outcome of COVID-19 Egyptian Patients

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Abstract

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  1. SciScore for 10.1101/2021.06.14.21258855: (What is this?)

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

    Table 1: Rigor

    EthicsConsent: Ethics: Verbal informed consent was obtained before enrolment from all participants or their first-degree relatives after explaining the details of the study.
    IRB: As such, approval for the conduction of the study was received from the Ain Shams University Faculty of Medicine Research Ethics Committee (REC).
    Sex as a biological variablePregnant women and patients with non-infectious causes of systemic inflammation that can induce PCT production, such as trauma, surgery, burn injury, and chronic kidney disease, were excluded.
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.

    Table 2: Resources

    Software and Algorithms
    SentencesResources
    Statistical methods: The IBM SPSS statistics program (V. 26.0, IBM Corp.,
    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: We detected the following sentences addressing limitations in the study:
    To our knowledge, our study is the first to explore the role of PCT-c as an indicator for dynamic changes in PCT to predict the outcome of hospitalized COVID-19 patients, but it has several limitations. The first issue is the small sample size and the disproportionate number of cases in the study groups. Second, we did not collect enough information about antibiotic treatment of patients or the results of their microbiological cultures. Third, we studied changes in PCT alone and did not account for the possibility that the relationship of PCT to other inflammatory markers could be more informative. Thus, further studies on larger samples and more clinical considerations, as well as correlation and comparison with other inflammatory markers, are required.

    Results from TrialIdentifier: No clinical trial numbers were referenced.


    Results from Barzooka: We found bar graphs of continuous data. We recommend replacing bar graphs with more informative graphics, as many different datasets can lead to the same bar graph. The actual data may suggest different conclusions from the summary statistics. For more information, please see Weissgerber et al (2015).


    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.

    Results from scite Reference Check: We found no unreliable references.


    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.