Pre-procedural testing improves estimated COVID-19 prevalence and trends

  1. Genevieve C. Pang
  2. Amy T. Hou
  3. Krizhna L. Bayudan
  4. Ethan A. Frank
  5. Jennifer Pastiglione
  6. Lorrin W. Pang

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Abstract

Background

COVID-19 positivity rates reported to the public may provide a distorted view of community trends because they tend to be inflated by high-risk groups, such as symptomatic patients and individuals with known exposures to COVID-19. This positive bias within high-risk groups has also varied over time, depending on testing capability and indications for being tested. In contrast, throughout the pandemic, routine COVID-19 screening tests for elective procedures and operations unrelated to COVID-19 risk have been administered by medical facilities to reduce transmission to medical staffing and other patients. We propose the use of these pre-procedural COVID-19 patient datasets to reduce biases in community trends and better understand local prevalence.

Methods

Using patient data from the Maui Medical Group clinic, we analyzed 12,640 COVID-19 test results from May 1, 2020 to March 16, 2021, divided into two time periods corresponding with Maui’s outbreak.

Results

Mean positivity rates were 0.1% for the pre-procedural group, 3.9% for the symptomatic group, 4.2% for the exposed group, and 2.0% for the total study population. Post-outbreak, the mean positivity rate of the pre-procedural group was significantly lower than the aggregate group (all other clinic groups combined). The positivity rates of both pre-procedural and aggregate groups increased over the study period, although the pre-procedural group showed a smaller rise in rate.

Conclusions

Pre-procedural groups may produce different trends compared to high-risk groups and are sufficiently robust to detect small changes in positivity rates. Considered in conjunction with high-risk groups, pre-procedural marker groups used to monitor understudied, low-risk subsets of a community may improve our understanding of community COVID-19 prevalence and trends.

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  1. ScreenIT

    SciScore for 10.1101/2022.04.13.22273200: (What is this?)

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

    Table 1: Rigor

    EthicsIRB: The Hawaii Department of Health’s Institutional Review Board reviewed this study as a project in partnership with MMG.
    Consent: The project was approved and qualified as exempt research under 45 CFR 46.116(d) of the Department of Health and Human Services, waiving informed consent based on the minimal risk associated with de-identified data used in this study.
    Sex as a biological variablenot detected.
    Randomizationnot detected.
    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:
    Study limitations: Although pre-procedural groups do not contain the same biases as high-risk groups, this group may not approximate a randomized sample in several critical ways. First, pre-procedural patients may behave more cautiously and limit potential exposures in anticipation of scheduled procedures, negatively biasing the positivity rates of this group. If this bias is consistent over time, the positivity rates of this group could still be used to detect relative changes in trends. One could also circumvent this potential bias by focusing on patients admitted to the emergency room (ER) for reasons unrelated to COVID-19 (e.g., automobile accidents, lacerations, or burns). Unlike pre-procedural patients, ER patients are screened for COVID-19 onsite and lack the opportunity to modify their behaviors. Second, the demographics of pre-procedural groups may differ from the clinic population. As was observed in this study (Table 1), pre-procedural groups likely contain a greater proportion of older patients in need of corrective procedures. Weighted adjustments would be required to reconstruct a more demographically representative sample, although these correction factors may be minimal5. Additionally, if such distortions are consistent over time, correction factors could still allow for trend analysis and mathematical modeling of COVID-19 positivity rates. Third, the classification of patient groups in this study is based on the chief reason for testing. This method served to...

    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.

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  2. Version published to 10.1101/2022.04.13.22273200v1 on medRxiv