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510(k) Data Aggregation

    K Number
    K052239
    Manufacturer
    Date Cleared
    2005-09-21

    (35 days)

    Product Code
    Regulation Number
    888.3030
    Reference & Predicate Devices
    N/A
    Why did this record match?
    Device Name :

    EBI DYNAFIX VISION FOOTPLATE SYSTEM

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

    The EBI® DynaFix® Vision® FootPlate System intended for use in the treatment of the HDP by na in and other osteotomies, arthrodesis, fracture fixation, and other bone bond tone able to treatment by the use of the external fixation modality.

    Device Description

    External Fixation Device

    AI/ML Overview

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

    Acceptance CriteriaReported Device Performance
    Conforms to design specifications"the FootPlate System conforms to its design specifications."
    Functions as intended"In all instances, the FootPlate System functioned as intended"
    Test results obtained as expected"the test results obtained were as expected."
    Mechanically sound (static)Mechanical testing verified static design specifications.
    Mechanically sound (fatigue)Mechanical testing verified fatigue design specifications.
    Safe and effective as predicate devices (DFS and Vision Systems)"Performance data demonstrate that the FootPlate System is as safe and effective as the DFS System and Vision System."
    No new issues of safety or effectiveness compared to predicate devices"The minor technological differences... raise no new issues of safety or effectiveness."

    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 describes mechanical testing rather than a study involving human or animal subjects and data provenance. For the mechanical testing performed:

    • Sample Size for Test Set: Not explicitly stated as a number of devices. The study mentions that an "Engineering Rationale was written to demonstrate that the mechanical testing conducted represented the worst case construct and why further testing on the additional sizes of FootPlate System components is unnecessary." This implies that representative samples of the FootPlate System, likely the worst-case configuration, were tested.
    • Data Provenance: Not applicable as this was mechanical testing of a medical device, not a clinical study on patients.

    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)

    Not applicable. Ground truth as typically understood in studies involving expert review (e.g., medical image analysis) is not relevant for this type of mechanical device testing. The "ground truth" here is the physical performance and adherence to engineering specifications, which is assessed through standardized mechanical tests.

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

    Not applicable. Adjudication methods are typically used in studies where human experts are making judgments that need to be reconciled (e.g., clinical diagnoses). This was mechanical testing, where performance is measured objectively.

    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

    Not applicable. This is a 510(k) summary for a mechanical external fixation device, not a diagnostic or AI-powered device. Therefore, an MRMC study or AI assistance evaluation is not relevant.

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

    Not applicable. This is not an AI algorithm or software device.

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

    The "ground truth" for this device's performance is its physical and mechanical properties measured against predefined design specifications and engineering standards. This includes:

    • Static design specifications
    • Fatigue design specifications
    • Expected functional performance

    These aspects are evaluated through controlled mechanical testing.

    8. The sample size for the training set

    Not applicable. This is a mechanical device, not a machine learning model, so there is no "training set."

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

    Not applicable, as there is no training set for this type of device.

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