The COVID-19 pandemic and temporal change in metabolic risk factors for cardiovascular disease: A natural experiment within the HELIUS study

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Abstract

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  1. SciScore for 10.1101/2021.11.25.21266856: (What is this?)

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

    Table 1: Rigor

    EthicsIRB: The HELIUS study has been approved by the AMC Ethical Review Board.
    Consent: All participants provided written informed consent.
    Sex as a biological variableBaseline data were collected between 2011 and 2015 among 24,789 Dutch, South-Asian Surinamese, African Surinamese, Ghanaian, Moroccan, and Turkish origin women and men aged 18-70 years living in Amsterdam.
    RandomizationPotential participants were sampled with a simple random sampling method from the municipality registry, after stratification by ethnicity as defined by registered country of birth [21].
    Blindingnot detected.
    Power Analysisnot detected.

    Table 2: Resources

    No key resources detected.


    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:
    While natural experiments are generally considered strong [29], some limitations persist. First, response bias may have occurred [20] affecting generalizability to the general population. Moreover, random assignment to the control or exposed group was not possible, resulting in baseline differences between these groups. This may be due to phasing of the study, or selective drop-out among exposed participants. For instance, if only healthy participants were comfortable with being examined during the pandemic, this would result in a healthy subset of participants. We attempted to account for these differences through IPW, yet, this method does not account for potentially relevant unmeasured confounders. Despite this limitation, we chose IPW as our method to adjust for baseline differences and possible selective drop-out as it uses the entire sample, whereas propensity score matching would have led to a loss of cases, thereby negatively affecting our power [25]. Moreover, we could not adjust for differences in follow-up time, as this is a direct result of the restrictive measures. Yet, this may have affected variables that change with age, e.g. eGFR and SBP. On average, SBP increases with 7 mmHg every ten years [30] and eGFR decreases with 1 mL/min/year rate [31]. Given that the difference in follow-up time between the control and exposed group is only several months, this is thus unlikely to completely explain our findings. Furthermore, the effect of the mediators may have been...

    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

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