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510(k) Data Aggregation

    K Number
    K990796
    Date Cleared
    1999-04-28

    (49 days)

    Product Code
    Regulation Number
    866.5660
    Reference & Predicate Devices
    N/A
    Predicate For
    AI/MLSaMDIVD (In Vitro Diagnostic)TherapeuticDiagnosticis PCCP AuthorizedThirdpartyExpeditedreview
    Intended Use

    Enzyme linked immunosorbent assay method for the semi-quantitative determination of specific IgG autoantibodies to Pr 3 in human serum. The results of the anti-Pr 3 assay can be used as an aid in the diagnosis of autoimmune vasculiticles including Wegener's granulomatosis and other conditions associated with elevated anti-neutrophil cytoplasmic antibodies (c-ANCA). For in vitro diagnostic use only.

    Device Description

    Enzyme linked immunosorbent assay method for the semi-quantitative determination of specific IgG autoantibodies to Pr 3 in human serum. This device is designed for use with the Hycor Hy. Tec Automated EIA instrument.

    AI/ML Overview

    The provided text does not contain detailed information about specific acceptance criteria and the results of a study designed to prove the device meets those criteria. The document is primarily a 510(k) clearance letter from the FDA for two devices, the "Cogent Autostat™ II Anti-PR3 ELISA" and the "Hycor Hy-Tec Anti-PR3 ELISA". It confirms that these devices are substantially equivalent to legally marketed predicate devices.

    However, based on the general nature of an ELISA for autoantibodies, particularly for conditions like Wegener's granulomatosis, we can infer some aspects of what such a submission would entail and what types of studies would be done.

    Here's an attempt to answer your questions by inferring from typical IVD submissions and the provided limited text:

    1. Table of acceptance criteria and the reported device performance:
      The document does not specify exact acceptance criteria or reported device performance metrics in a numbered or statistical format. For an ELISA kit, typical performance metrics would include:

      • Sensitivity: The ability of the test to correctly identify individuals with the disease (true positives).
      • Specificity: The ability of the test to correctly identify individuals without the disease (true negatives).
      • Accuracy: The overall correctness of the test results.
      • Precision/Reproducibility: The ability of the test to produce consistent results when repeated.
      • Assay Range/Linearity: The concentration range over which the assay can accurately measure the analyte.
      • Interference: Lack of significant impact from common interfering substances in serum.

      Without a detailed performance study section, we cannot populate this table with specific numbers. The FDA letter only states "substantial equivalence."

    2. Sample size used for the test set and the data provenance (e.g. country of origin of the data, retrospective or prospective):
      The document does not provide this information. For substantial equivalence, studies would typically involve a prospective or retrospective collection of patient samples (both diseased and healthy controls or other disease states) to assess performance against a recognized reference method or clinical diagnosis. The country of origin and specific study design (prospective/retrospective) are not mentioned.

    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):
      The document does not specify the number or qualifications of experts used to establish ground truth. For diseases like Wegener's Granulomatosis, ground truth would likely be established by a combination of clinical diagnosis, physician assessment (e.g., rheumatologists, nephrologists), and possibly biopsy results, rather than solely by a specific number of individual experts interpreting imaging or similar.

    4. Adjudication method (e.g. 2+1, 3+1, none) for the test set:
      Not specified in the document. Ground truth establishment for a diagnostic test like this would likely rely on consensus clinical diagnosis, rather than a specific adjudication method for interpreting individual "reads" as might be seen with imaging studies.

    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:
      This question is not applicable to the device described. The "Cogent Autostat™ II Anti-PR3 ELISA" and "Hycor Hy-Tec Anti-PR3 ELISA" are enzyme-linked immunosorbent assay (ELISA) kits, which are in vitro diagnostic laboratory tests for detecting specific antibodies in human serum. They do not involve human "readers" in the context of interpreting images or complex data where AI assistance would be relevant. There is no AI component mentioned or implied for these devices.

    6. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done:
      This question is also not applicable. These are diagnostic kits, not algorithms. Their performance is their standalone performance in terms of detecting antibodies in a sample.

    7. The type of ground truth used (expert consensus, pathology, outcomes data, etc):
      While not explicitly stated, for conditions like Wegener's Granulomatosis associated with ANCA, the ground truth would typically be:

      • Clinical Diagnosis: Established by physicians based on a combination of patient symptoms, physical examination, laboratory findings (including ANCA testing and other markers), and often biopsy results (pathology) confirming vasculitis or granuloma formation.
      • Outcomes Data: In some cases, long-term patient outcomes are used to confirm diagnosis, but initial ground truth for a diagnostic test is usually based on established diagnostic criteria.
    8. The sample size for the training set:
      The document does not mention a training set, as these are traditional IVD kits, not AI algorithms that require training data.

    9. How the ground truth for the training set was established:
      Not applicable, as no training set for an AI algorithm is involved.

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