Next generation plasma proteome profiling of COVID-19 patients with mild to moderate symptoms

  1. Wen Zhong
  2. Ozlem Altay
  3. Muhammad Arif
  4. Fredrik Edfors
  5. Levent Doganay
  6. Adil Mardinoglu
  7. Mathias Uhlen
  8. Linn Fagerberg

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Abstract

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  1. Version published to 10.1016/j.ebiom.2021.103723
  2. ScreenIT

    SciScore for 10.1101/2021.06.15.21258940: (What is this?)

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

    Table 1: Rigor

    EthicsConsent: Written informed consent was obtained from all participants before the initiation of any trial-related procedures.
    IRB: The study was approved by the ethics committee of Istanbul Medipol University, Istanbul, Turkey, and retrospectively registered at https://clinicaltrials.gov/ with Clinical Trial ID: NCT04573153.
    IACUC: The study protocol conforms to the ethical guidelines of the 1975 Declaration of Helsinki.
    Sex as a biological variablenot detected.
    RandomizationParticipants: A total of 50 patients were randomly selected from a clinical trial cohort of 93 patients over 18 years of age, who had a PCR-confirmed COVID-19 test within the previous 24 h and were in stable condition not requiring hospitalization.
    Blindingnot detected.
    Power Analysisnot detected.

    Table 2: Resources

    Software and Algorithms
    SentencesResources
    The study was approved by the ethics committee of Istanbul Medipol University, Istanbul, Turkey, and retrospectively registered at https://clinicaltrials.gov/ with Clinical Trial ID: NCT04573153.
    https://clinicaltrials.gov/
    suggested: (ClinicalTrials.gov, RRID:SCR_002309)
    The analytical performance of each of the protein assays included in the panel is carefully validated based on specificity, sensitivity, dynamic range, precision, scalability, endogenous interference and detectability (http://www.olink.com).
    http://www.olink.com
    suggested: (Olink Bioscience, RRID:SCR_003899)
    Statistical Analysis: All data analysis and visualization was performed using R (v3.6.3)(R Development Core Team, 2021)
    R Development Core
    suggested: (R Project for Statistical Computing, RRID:SCR_001905)

    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: We found the following clinical trial numbers in your paper:

    IdentifierStatusTitle
    NCT04573153RecruitingMetabolic Cofactor Supplementation and Hydroxychloroquine Co…

    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.

    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.

  3. Version published to 10.1101/2021.06.15.21258940v1 on medRxiv