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510(k) Data Aggregation

    K Number
    K030701
    Date Cleared
    2003-09-09

    (187 days)

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

    An enzyme linked immunoassay (ELISA) for the detection and semi-quantitation of IgG antibodies to ß2-GP1, as an aid in assessing the risk of thrombosis in patients with Systemic Lupus Erythematosus (SLE) or lupus like disorders

    Device Description

    An enzyme linked immunoassay (ELISA) for the detection and semi-quantitation of IgG antibodies to ß2-GP1

    AI/ML Overview

    The provided text is an FDA 510(k) clearance letter for the "ImmuLisa Anti-Beta2 Glycoprotein I (ß2GP1) IgG ELISA" device. This document primarily focuses on the regulatory clearance and does not contain the detailed study information typically found in a clinical study report or a 510(k) submission summary that would describe acceptance criteria and study results.

    Therefore, I cannot provide the requested information. The document does not describe:

    1. Acceptance criteria or device performance table.
    2. Sample size for test set or data provenance. This information would be in the validation study data, not the clearance letter.
    3. Number of experts, qualifications, or ground truth establishment for the test set. This is not within the scope of this FDA letter.
    4. Adjudication method.
    5. MRMC comparative effectiveness study. This device is an ELISA kit, not an AI-assisted diagnostic tool, so this question is not applicable.
    6. Standalone performance. While the device performs in a standalone manner, the specific performance metrics (sensitivity, specificity, etc.) and the study details proving them are not in this letter.
    7. Type of ground truth used. This would be in the study design document.
    8. Sample size for the training set. This device is an ELISA kit, which typically does not involve a "training set" in the machine learning sense. Its development involves standardization and validation with known positive and negative samples.
    9. How ground truth for the training set was established. (See point 8).

    The document is a regulatory approval letter based on a submission that would contain such data, but the letter itself does not detail it.

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