Patient Characteristics in Cases of Reinfection or Prolonged viral shedding in SARS-CoV-2

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Abstract

Importance

As testing options increase for COVID-19, their interpretability is challenged by the increasing variety of clinical contexts in which results are obtained. In particular, positive COVID-19 diagnostic (RT-PCR) tests that occur after a patient has seroconverted may be indicative of reinfection. However, in the absence of SARS-CoV-2 sequence data, the possibility of prolonged viral shedding may not be excluded. We highlight a testing pattern that identifies such cases and study its statistical power in identifying potential reinfection. We also study the medical records of patients that matched the pattern.

Objective

To describe the frequency and demographic information of people with a testing pattern indicative of SARS-CoV-2 reinfection.

Design

We examined 4.2 million test results from a large national health insurer in the United States. Specifically, we identified the pattern of a positive RT-PCR test followed by a positive IgG test, again followed by a positive RT-PCR.

Setting

Data from outpatient laboratories across the United States was joined with claims data from a single large commercial insurer’s administrative claims database.

Participants

Study participants are those whose insurance, either commercial or Medicare, is provided by a single US based insurer.

Exposures

People who received at least two positive diagnostic tests via RT-PCR for SARS-Cov-2 separated by 42 or more days with at least one serological test (IgG) indicating the presence of antibodies between diagnostic tests.

Main Outcomes and Measures

Count and characteristics of people with the timeline of three tests as described in Exposures.

Results

We identified 79 patients who had two positive RT-PCR tests separated by more than six weeks, with a positive IgG test in between. These patients tended to be older than those COVID-19 patients without this pattern (median age 56 vs. 42), and they exhibited comorbidities typically attributed to a compromised immune system and heart disease.

Conclusions and Relevance

While the testing pattern alone was not sufficient to distinguish potential reinfection from prolonged viral shedding, we were able to identify common traits of the patients identified through the pattern.

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  1. SciScore for 10.1101/2021.05.14.21257231: (What is this?)

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

    Table 1: Rigor

    Ethicsnot detected.
    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: An explicit section about the limitations of the techniques employed in this study was not found. We encourage authors to address study limitations.

    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.