Public health impact of poor sleep on COVID-19, influenza and upper respiratory infections

  1. S.E. Jones
  2. F.I. Maisha
  3. S. Strausz
  4. B. Cade
  5. A. Tervi
  6. V. Helaakoski
  7. M. Broberg
  8. V. Lammi
  9. J.M. Lane
  10. S. Redline
  11. R. Saxena
  12. H.M. Ollila

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Abstract

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  1. Version published to 10.1016/j.sleep.2022.05.369
  2. ScreenIT

    SciScore for 10.1101/2022.02.16.22271055: (What is this?)

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

    Table 1: Rigor

    NIH rigor criteria are not applicable to paper type.

    Table 2: Resources

    Antibodies
    SentencesResources
    Diagnoses were primarily by PCR (N=3,424), with a small proportion of samples diagnosed through antigen testing (N=9), or antibody testing (N=6), and 57 samples with a missing diagnosis type.
    antigen testing ( N=9) ,
    suggested: None
    Software and Algorithms
    SentencesResources
    When a study participant is recruited, their entire medical record is linked into the FinnGen database and not just subsequent healthcare provider visits, allowing a detailed understanding of their medical history.
    FinnGen
    suggested: (Open Targets Genetics Portal, RRID:SCR_021701)
    Samples were genotyped using Illumina and Affymetrix chip arrays (Illumina Inc., San Diego, and Thermo Fisher Scientific, Santa Clara, CA, USA) and imputed to GRCh38/hg38 using Beagle v4.153 with the SISu v3.0 reference panel, consisting of 3,775 whole genome-sequenced Finnish individuals54 (see https://dx.doi.org/10.17504/protocols.io.nmndc5e for the complete imputation and QC protocol).
    Beagle
    suggested: (BEAGLE, RRID:SCR_001789)
    These GWA analyses were performed using REGENIE55 v2.0.2 and in the model-building step (step 1) were adjusted for age at follow-up end (2019/12/31) or death, sex, genotyping batch and the first 10 genetic principal components.
    REGENIE55
    suggested: None
    We performed this analysis using the Python module “lifelines” (v0.26.0)56 with Python (v3.8.11 for FinnGen, v3.7.11 for UK Biobank).
    Python
    suggested: (IPython, RRID:SCR_001658)

    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:
    We note the following limitations, welcome feedback from the scientific community and will aim to address some of these issues in future studies in this line of research. First of all, FinnGen endpoints were identified using hospital records only, and consequently results of survival analyses are biased towards more serious cases of the prior (insomnia) endpoint. In comparison, in the UK Biobank diagnoses were captured in hospital and primary care data. It is therefore possible that the differences in hazard ratio we see between the two cohorts represent a) greater statistical power due to more severe insomnia diagnosis, b) a real difference in effect of insomnia on more severe (FinnGen) and less severe (UK Biobank) respiratory infections, c) differences between the cohort demographics or d) a combination of these factors. Confounding this issue is that the UK Biobank suffers from ascertainment bias, resulting in a cohort that is, on average, healthier and less socioeconomically deprived than the general UK population48 and it is likely, though not yet reported, that the FinnGen study also suffers from this bias. The insomnia prevalence that we observed (0.9% in FinnGen and 3.8% in UKB; Supp Table 5) point to low ascertainment in these cohorts compared to estimates of insomnia prevalence (7.9% in the UK49 and up to 11.7% in Finland50). While ascertainment bias has been shown to exaggerate the effects of a prior endpoint on survival time51, it is not currently known how this a...

    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.

    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 10.1101/2022.02.16.22271055v1 on medRxiv