Impact of COVID-19 mitigation measures on the incidence of preterm birth: a national quasi-experimental study

  1. Jasper V Been
  2. Lizbeth Burgos Ochoa
  3. Loes C M Bertens
  4. Sam Schoenmakers
  5. Eric A P Steegers
  6. Irwin K M Reiss

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Abstract

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  1. Version published to 10.1016/s2468-2667(20)30223-1
  2. ScreenIT

    SciScore for 10.1101/2020.08.01.20160077: (What is this?)

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

    Table 1: Rigor

    Institutional Review Board StatementConsent: According to standard procedures and under strict conditions that were fulfilled, RIVM allows anonymised data registered as part of the screening programme to be used for research purposes with waiver of consent.
    Randomizationnot detected.
    Blindingnot detected.
    Power AnalysisWe anticipated that this would provide ample statistical power to identify an association between the COVID-19 mitigation measures and preterm births in the Netherlands, if present.
    Sex as a biological variablenot 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:
    Our study also has limitations. Given the unanticipated nature of the COVID-19 pandemic and associated mitigation measures, we had to use a retrospective approach to data collection. As in any registry-based study, there may have been registration errors, and a very small proportion of individuals had missing data. Cross-validation against Perined suggested very little temporal variation in comparability of the data or missing variables, which − even if present − should have been captured by our difference-in-regression-discontinuity design, making any impact on our effect estimation unlikely. There was a slight underrepresentation of extremely preterm and ELBW births in our dataset as compared to Perined. This was anticipated as a result of three issues: 1. aggregated birth weight data for Perined included babies born between 22+0 and 23+6 weeks, hence explaining overrepresentation of ELBW babies in Perined; 2. Perined data include stillbirths; and 3. extremely preterm babies are at increased risk of dying in the first few days after birth.24 For obvious reasons, stillborn babies and those dying shortly after birth did not contribute data to the neonatal screening programme and hence were missing from our dataset. Importantly, our validation indicates that this relative underrepresentation was not differential over time and is therefore unlikely to have influenced our findings. If anything, survival of preterm babies improved over the study period, which would have biased ou...

    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

    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 10.1101/2020.08.01.20160077v1 on medRxiv