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Peer Reviews (296)

Published on in Vol 6 (2025)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/83479, first published .
Peer Review of “Real-World Performance of COVID-19 Antigen Tests: Predictive Modeling and Laboratory-Based Validation”

Peer Review of “Real-World Performance of COVID-19 Antigen Tests: Predictive Modeling and Laboratory-Based Validation”

Peer Review of “Real-World Performance of COVID-19 Antigen Tests: Predictive Modeling and Laboratory-Based Validation”

Authors of this article:

Gerald Kost1
Article Authors Cited by Tweetations Metrics


    This is a peer-review report for “Real-World Performance of COVID-19 Antigen Tests: Predictive Modeling and Laboratory-Based Validation.”


    General Comments

    This paper [1] introduces a novel approach to speeding COVID-19 antigen test deployment, possibly during the next pandemic, whether it be a COVID-19 variant or a new pathogen that arises.

    Specific Comments

    Major Comments

    1. The authors’ clinical conclusions based on their prediction theory are overly optimistic.

    2. The authors can explore actual clinical evaluations to determine the robustness of their prediction modeling.

    3. Thus, the paper merits publication, providing the limitations are more clearly described and the conclusions are limited to the mathematical results for which the authors have proven their claims theoretically. Extension to clinical applicability is a different story yet to be told.

    4. The authors should be encouraged to move forward in view of the need and the poor performance of COVID-19 rapid antigen tests during the pandemic because of low sensitivity, a lack of deep understanding, and the “prevalence boundary,” a measure of when the rate of false omissions becomes too high and false negatives spread disease.

    Minor Comments

    5. Needs English grammar review. This could be achieved by using an artificial intelligence editor.

    Conflicts of Interest

    None declared.

    1. Bosch M, Garcia D, Rudtner L, et al. Real-world performance of COVID-19 antigen tests: predictive modeling and laboratory-based validation. JMIRx Med. 2025;6:e68376. [CrossRef]

    Edited by Fuqing Wu; This is a non–peer-reviewed article. submitted 03.Sep.2025; accepted 03.Sep.2025; published 06.Oct.2025.

    Copyright

    © Gerald Kost. Originally published in JMIRx Med (https://med.jmirx.org), 6.Oct.2025.

    This is an open-access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work, first published in JMIRx Med, is properly cited. The complete bibliographic information, a link to the original publication on https://med.jmirx.org/, as well as this copyright and license information must be included.