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510(k) Data Aggregation

    K Number
    K013900
    Date Cleared
    2001-12-21

    (28 days)

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

    For in vitro use in verifying the calibration range of the VITROS Immunodiagnostic System when used for the measurement of Vitamin B12.

    Device Description

    The VITROS Immunodiagnostic System uses luminescence as the signal in the quantitative and semi-quantitative determination of selected analytes in human body fluids, commonly serum, plasma and urine. Coated microwells are used as the solid phase separation system. The system is comprised of three main elements: 1. The VITROS ECi Immunodiagnostic Products (in this case VITROS Immunodiagnostic Products Range Verifiers, which are used along with VITROS Immunodiagnostic Products Reagent Pack and VITROS Immunodiagnostic Products Calibrators by the VITROS ECi Immunodiagnostic System to verify the performance of the VITROS assay). 2. The VITROS ECi Immunodiagnostic System instrumentation, which provides automated use of the immunoassay kits. 3. Common reagents used by the VITROS ECi System in each assay.

    AI/ML Overview

    The provided text describes a 510(k) summary for a medical device called "VITROS Immunodiagnostic Products Vitamin B12 Range Verifiers." This document establishes the device's substantial equivalence to a predicate device, but it does not contain information about acceptance criteria or a study that proves the device meets specific performance criteria through testing of a novel device.

    The document primarily focuses on:

    • Device Description: What the device is and how it functions generally within the VITROS Immunodiagnostic System.
    • Intended Use: For in vitro use in verifying the calibration range of the VITROS Immunodiagnostic System for Vitamin B12 measurement.
    • Comparison to Predicate Device: Table 1 lists the similarities and differences between the new device and the predicate device, specifically regarding intended use, matrix composition, and target concentrations of the range verifier levels.
    • Conclusion of Substantial Equivalence: The document asserts that the new device is substantially equivalent to the predicate device based on physical properties and intended uses.

    Therefore, I cannot provide the requested information. The document explicitly focuses on demonstrating substantial equivalence, not on presenting performance data from a primary study of a new device against acceptance criteria.

    Specifically, the following information is not available in the provided text:

    1. A table of acceptance criteria and the reported device performance: No specific acceptance criteria (e.g., accuracy, precision, sensitivity, specificity, agreement rates) or detailed performance results are presented. The "Range Verifier levels" in Table 1 are target concentrations for the verification materials, not performance metrics.
    2. Sample size used for the test set and the data provenance: Not applicable, as no performance study data is included.
    3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts: Not applicable.
    4. Adjudication method (e.g. 2+1, 3+1, none) for the test set: Not applicable.
    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 device is a range verifier for an immunoassay system, not an AI-assisted diagnostic tool. Therefore, an MRMC study is not relevant and not mentioned.
    6. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done: This pertains to AI/algorithm performance, which is not applicable to this device.
    7. The type of ground truth used (expert consensus, pathology, outcomes data, etc.): Not applicable, as no performance study data is included.
    8. The sample size for the training set: Not applicable, as this device is not based on a machine learning model requiring a training set.
    9. How the ground truth for the training set was established: Not applicable.
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