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510(k) Data Aggregation

    K Number
    K981120
    Date Cleared
    1998-08-21

    (147 days)

    Product Code
    Regulation Number
    866.3235
    Reference & Predicate Devices
    N/A
    Predicate For
    N/A
    AI/MLSaMDIVD (In Vitro Diagnostic)TherapeuticDiagnosticis PCCP AuthorizedThirdpartyExpeditedreview
    Intended Use

    This test system is designed to detect IgG antibodies to EBV EA in human serum specimens. This test system is intended to be used as an aid in the diagnosis of infectious mononucleosis. The performance characteristics have not been established to aid in the diagnosis of acute IM.

    Device Description

    Not Found

    AI/ML Overview

    This document is a 510(k) clearance letter from the FDA for a diagnostic device, not a study report. Therefore, it does not contain the detailed information required to answer all parts of your request about acceptance criteria and a study proving the device meets them.

    However, based on the information provided in the document (specifically the "Indications for Use" from page 1 and the general nature of a 510(k) submission), I can infer some aspects and highlight what is not present:

    Information available from the document:

    • Device Name: Zeus Scientific, Inc., anti-EBV EA IgG ELISA Test System
    • Intended Use: To detect IgG antibodies to EBV EA in human serum specimens. Intended to be used as an aid in the diagnosis of infectious mononucleosis.

    Here's what can be extracted and what cannot:

    1. A table of acceptance criteria and the reported device performance:

      • Cannot be provided. This document is an FDA clearance letter confirming substantial equivalence to a predicate device, not a detailed technical report of the device's performance study. It does not contain tables of acceptance criteria or specific performance metrics (like sensitivity, specificity, accuracy against a gold standard). The general assumption in a 510(k) is that the device performs "as well as" or "similarly to" the predicate.
    2. Sample size used for the test set and the data provenance (e.g. country of origin of the data, retrospective or prospective):

      • Cannot be provided. The document does not specify the sample size, type of study (retrospective/prospective), or data provenance for any clinical trial that may have been performed.
    3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts (e.g. radiologist with 10 years of experience):

      • Not applicable/Cannot be provided directly. For an ELISA diagnostic test, "ground truth" is typically established by comparing results to a reference method or clinical diagnosis, not by expert consensus in the same way imaging studies are. The document doesn't detail how the ground truth for any validation samples was established or the number/qualifications of individuals involved.
    4. Adjudication method (e.g. 2+1, 3+1, none) for the test set:

      • Not applicable/Cannot be provided. Adjudication methods like 2+1 or 3+1 are primarily relevant for subjective assessments, typically in imaging studies where discordant expert opinions need to be resolved. This is an ELISA test, which produces objective numerical results, so such adjudication is not generally used.
    5. If a multi reader multi case (MRMC) comparative effectiveness study was done, If so, what was the effect size of how much human readers improve with AI vs without AI assistance:

      • Not applicable. This device is an in-vitro diagnostic (IVD) ELISA test, not an AI-powered diagnostic tool requiring human interpretation or an MRMC study. It provides a direct measurement (IgG antibody levels).
    6. If a standalone (i.e. algorithm only without human-in-the loop performance) was done:

      • Partially applicable. An ELISA test is inherently a "standalone" assay in that the result is generated by the biochemical reaction of the test system, without real-time human input influencing the result generation itself. However, the document does not provide performance data for such a standalone assessment.
    7. The type of ground truth used (expert consensus, pathology, outcomes data, etc):

      • Cannot be definitively stated from the document. For an ELISA for infectious disease, the ground truth would likely be established by a combination of:
        • Clinical diagnosis of infectious mononucleosis (based on symptoms, other lab tests).
        • Results from other established reference methods for EBV antibody detection.
        • Patient outcomes data (e.g., resolution of symptoms) might indirectly contribute, but less directly for establishing assay accuracy.
      • The document states, "The performance characteristics have not been established to aid in the diagnosis of acute IM." This implies that the device's utility specifically for acute IM diagnosis was not fully proven by the submitted data for clearance.
    8. The sample size for the training set:

      • Not provided. This document does not mention a training set, as a traditional machine learning model would have. ELISA kits are developed through formulation and calibration, not typically "trained" on datasets in the AI sense.
    9. How the ground truth for the training set was established:

      • Not applicable. As above, no training set in the AI/ML sense is mentioned or implied for an ELISA test.

    In summary: The provided document is an FDA clearance letter for a medical device (an ELISA test kit) that confirms its substantial equivalence to a legally marketed predicate device. It is not a detailed scientific study report that would contain the specific performance data, study methodologies, and ground truth establishment details you are asking for. Such information would typically be found in the manufacturer's 510(k) submission summary or detailed clinical study reports, which are not part of this public clearance letter.

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