Structural and metabolic brain abnormalities in COVID-19 patients with sudden loss of smell

  1. Maxime Niesen
  2. Nicola Trotta
  3. Antoine Noel
  4. Tim Coolen
  5. Georges Fayad
  6. Gil Leurkin-Sterk
  7. Isabelle Delpierre
  8. Sophie Henrard
  9. Niloufar Sadeghi
  10. Jean-Christophe Goffard
  11. Serge Goldman
  12. Xavier De Tiège

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Abstract

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  1. ScreenIT

    SciScore for 10.1101/2020.10.18.20214221: (What is this?)

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

    Table 1: Rigor

    Institutional Review Board StatementIRB: Participants contributed to the corresponding studies approved by the institutional Ethics Committee after written informed consent (References: P2020/204, CCB: B4062020000031; P2017/541, CCB: B406201734197).
    Consent: Participants contributed to the corresponding studies approved by the institutional Ethics Committee after written informed consent (References: P2020/204, CCB: B4062020000031; P2017/541, CCB: B406201734197).
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.
    Sex as a biological variableFor PET data analyses, a PET-MR data set acquired in the context of other neuroimaging studies and composed of twenty-six healthy subjects (5 females, 21 males, mean age: 35 years, age range: 22-52 years) without any history of COVID-19, smell or taste disorders was used as control group.

    Table 2: Resources

    Software and Algorithms
    SentencesResources
    Final reports were then discussed with neurologists (S.G., X.D.T.), neuroradiologist (N.S.), otorhinolaryngologists (M.N., A.N., G.F.), and internists (S.H., J-C.G.) PET data analysis: FDG-PET data were analyzed using the voxel-based Statistical Parametric Mapping software (SPM8, http://www.fil.ion.ucl.ac.uk/spm/, Wellcome Trust Centre for Neuroimaging, London, UK) based on conventional subtractive and correlation analyses previously used by our group and described in details elsewhere.[
    http://www.fil.ion.ucl.ac.uk/spm/
    suggested: (IBASPM: Individual Brain Atlases using Statistical Parametric Mapping Software, RRID:SCR_007110)
    For significant voxels, regression plots and associated slope coefficients/p-values (Pearson’s correlation) between glucose metabolism and covariates of interest were obtained in Matlab R2017a (MathWorks Inc.).
    Matlab
    suggested: (MATLAB, RRID:SCR_001622)

    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:
    Limitations of the study: PET-MR data were acquired in patients at different moments after the onset of dysosmia with no longitudinal neuroimaging follow-up. Although this approach proved its value in correlation analyses with regional cerebral metabolism, it did not allow proper characterization of the chronology of structural and metabolic abnormalities in COVID-19-related dysosmia. This study did not include any objective evaluation of taste function as it was not available at our center at the start of the COVID-19 pandemic and was very difficult to obtain during this sanitary crisis. Considering that all but one patient complained about altered sense of taste, it would have been of great interest to investigate the brain metabolic changes specifically associated with dysgeusia. As discussed above, due to the recognized ambiguity between taste and smell perception,[23,24] we decided not to include any correlation analyses with the subjective evaluation of taste (i.e., visual analogue scale). For voxel-based FDG-PET data analyses, we relied on a group of healthy subjects who had undergone PET-MR imaging in the context of an unrelated neuroimaging study. This was due to the difficulty to perform neuroimaging research investigations in healthy subjects in an academic hospital environment during the ongoing COVID-19 pandemics. For that reason, healthy subjects did not undergo any objective or subjective evaluation of smell and taste at the time of the PET-MR data acquisition....

    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

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  2. Version published to 10.1007/s00259-020-05154-6
  3. Version published to 10.1101/2020.10.18.20214221v1 on medRxiv