How Strong is the Epidemiological Evidence for a Role of Vitamin D Levels on COVID-19 Infections and Mortality?

This article has been Reviewed by the following groups

Read the full article See related articles

Abstract

No abstract available

Article activity feed

  1. SciScore for 10.1101/2020.11.20.20235705: (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 variablenot detected.

    Table 2: Resources

    Software and Algorithms
    SentencesResources
    Data transformation (log and ln) and basic statistics calculations (Pearson correlation coefficient, Regression analysis, curve-fitting - calculation of best-fit trend line) were performed using Microsoft Excel as done previously [6,7].
    Microsoft Excel
    suggested: (Microsoft Excel, RRID:SCR_016137)

    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:
    As indicated by us and others the one-day data analysis had weaknesses [7, 8] and it would have been better had the analysis been not constrained by commonly used p-value cutoffs and improper model application on the biological data set, and preferably estimating the correlation post-peak of infections to reduce the effect of potential confounders of data reporting delay in infection and adverse outcome, and analyzing the correlation or regression at multiple points to arrive at potential dependable estimates. We now have COVID-19 data for the European countries for a larger time frame that by 26 July 2020 included a total of 1,829,634 cases and 179135 deaths accounting for the worldwide 11.11% cases and 27.45% deaths. The reanalysis of the data for an extended period indicates the potential problem of the analysis and model presented by Ilie et al. [5] which was previously predicted/indicated by us and others [7,8]. The simple linear regression modeling of the covariation of vitamin D levels with COVID-19 cases per million as suggested by the authors did not indicate a statistically significant correlation (p-value≥0.05) upto 8 Apr, which became statistically significant (at p-value cut off <0.05) by 12 April and stayed that way till 12 Jun then again become insignificant and remained so till the end of the analysis period, i.e., 26 July 2020. The correlation between deaths per million and vitamin D levels never ever reached the commonly used statistical significance level s...

    Results from TrialIdentifier: We found the following clinical trial numbers in your paper:

    IdentifierStatusTitle
    NCT04411446RecruitingCholecalciferol to Improve the Outcomes of COVID-19 Patients
    NCT04344041RecruitingCOvid-19 and Vitamin D Supplementation: a Multicenter Random…
    NCT04334005Not yet recruitingVitamin D on Prevention and Treatment of COVID-19


    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.