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510(k) Data Aggregation

    K Number
    K211895
    Device Name
    BC Reflex Uni Knee System
    Manufacturer
    Bodycad Laboratories, Inc.
    Date Cleared
    2021-08-20

    (60 days)

    Product Code
    HSX
    Regulation Number
    888.3520
    Type
    Traditional
    Panel
    Orthopedic (OR)
    Reference & Predicate Devices
    K210252,K102330,K203697
    Why did this record match?
    Reference Devices :

    K210252, K102330

    AI/MLSaMDIVD (In Vitro Diagnostic)TherapeuticDiagnosticis PCCP AuthorizedThirdpartyExpeditedreview
    Intended Use

    The patient-specific BC Reflex Unicompartmental knee arthroplasty (UKA) in patients with advanced knee osteoarthritis (OA) of the medial compartment with evidence of adequate healthy bone to support the implanted components. Candidates for unicompartmental knee replacement include those with:
    · joint impairment due to osteoarthritis or traumatic arthritis of the knee,
    · varus deformity of the knee, and
    · as an alternative to tibial osteotomy in patients with unicompartmental OA.
    The patient-specific BC Reflex Uni™ components fit within an envelope of dimensions that are specific to each patient. The BC Reflex Uni™ femoral component and tibial baseplate are intended for cemented fixation.

    Device Description

    The BC Reflex Uni™ Knee System is a patient-specific unicompartmental knee system that consists of femoral and tibial implants for replacement of the medial tibiofemoral compartment of the knee. The patient-specific femoral and tibial implants and single-use instruments are manufactured from CAD and CAM files generated from Bodycad software that are based on MRI or CT images of the patient's knee and surgeon input.

    AI/ML Overview

    This FDA 510(k) summary does not contain information about an AI-powered device or software. It pertains to a physical medical device, the BC Reflex Uni™ Knee System, which is a patient-specific unicompartmental knee system. The submission focuses on changes to sterilization methods and minor design updates, not on a diagnostic or prognostic algorithm.

    Therefore, I cannot provide the requested information regarding acceptance criteria and performance studies for an AI device. The document does not discuss:

    • Acceptance criteria related to AI performance metrics (e.g., sensitivity, specificity, accuracy).
    • Any study that proves an AI device meets such criteria.
    • Sample sizes for test sets, data provenance, expert qualifications, or adjudication methods for AI ground truth.
    • MRMC studies or standalone AI performance.
    • Training set details for an AI model.

    The "performance data" section (G) in the document refers to validation and verification activities for device sterilization, biocompatibility, packaging, and cleaning processes, which are standard for physical medical devices and unrelated to AI performance.

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