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510(k) Data Aggregation

    K Number
    K984604
    Manufacturer
    Date Cleared
    1999-02-02

    (36 days)

    Product Code
    Regulation Number
    862.1660
    Reference & Predicate Devices
    Predicate For
    N/A
    AI/MLSaMDIVD (In Vitro Diagnostic)TherapeuticDiagnosticis PCCP AuthorizedThirdpartyExpeditedreview
    Intended Use

    Architect Estradiol MasterCheck is intended for use in the verification of sensitivity, calibration linearity, and reportable range of the Estradiol assay on the Abbott Architect i System.

    Device Description

    Architect Estradiol MasterCheck Level 0 contains TRIS buffer with protein (bovine) stabilizers.

    Architect Estradiol MasterCheck Levels 1, 2, 3 and 4 contain estradiol prepared in TRIS buffer with protein (bovine) stabilizers.

    Preservative: Antimicrobial Agent.

    AI/ML Overview

    This document is a 510(k) summary for the Bio-Rad Architect Estradiol MasterCheck and does not contain the detailed information necessary to fully answer all aspects of your request regarding acceptance criteria and a study demonstrating the device meets those criteria.

    The document primarily focuses on establishing substantial equivalence to a predicate device for regulatory approval. It does not include:

    • A table of specific acceptance criteria (e.g., performance metrics, thresholds) for the device's function (sensitivity, calibration linearity, reportable range verification).
    • Details of a study proving the device meets specific predefined acceptance criteria.
    • Information about sample sizes for a test set, data provenance, expert ground truth establishment, adjudication methods, MRMC studies, or standalone algorithm performance.
    • Information about training sets or their ground truth establishment.

    However, based on the provided text, here's what can be extracted:

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

    The document does not provide a table of acceptance criteria with numerical performance targets or reported device performance against those targets. The "Statement of Intended Use" on page 0 and "Indications for Use" on page 4 define the intended functions, which implicitly represent the high-level criteria the device is expected to meet:

    Acceptance Criterion (Implicit)Reported Device Performance
    Verification of sensitivity of the Estradiol assayNot specified in this document
    Verification of calibration linearity of the Estradiol assayNot specified in this document
    Verification of reportable range of the Estradiol assayNot specified in this document

    2. Sample size used for the test set and the data provenance (e.g. country of origin of the data, retrospective or prospective)

    This information is not provided in the document.

    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)

    This information is not provided in the document.

    4. Adjudication method (e.g. 2+1, 3+1, none) for the test set

    This information is not provided in the document.

    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 document describes a diagnostic control product, not an AI-assisted diagnostic device, so an MRMC study comparing human readers with and without AI assistance is not applicable and therefore, not performed or mentioned here.

    6. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done

    This document describes a diagnostic control product, not an algorithm, so standalone algorithm performance is not applicable and therefore, not performed or mentioned here.

    7. The type of ground truth used (expert consensus, pathology, outcomes data, etc)

    This information is not provided in the document. For a control material, "ground truth" would typically refer to the known, characterized concentrations of analytes within the control materials themselves, established through validated reference methods. However, the details of how these concentrations were established are not described here.

    8. The sample size for the training set

    This document describes a diagnostic control product, not a machine learning algorithm that requires a training set. Therefore, this question is not applicable.

    9. How the ground truth for the training set was established

    This question is not applicable as it pertains to machine learning algorithms, which is not the subject of this document.

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