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510(k) Data Aggregation

    K Number
    K130590
    Manufacturer
    Date Cleared
    2013-04-22

    (46 days)

    Product Code
    Regulation Number
    888.3040
    Reference & Predicate Devices
    Why did this record match?
    Device Name :

    AAP CANNULATED SCREW 2.0

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

    The aap Cannulated Screw 2.0 is intended for fracture fixation of small and long bones and of the pelvis. The system is not intended for spinal use.

    Device Description

    Cannulated Screws are used for fixation of bone fragments, i.e., for treatment of bone fractures and other bone injuries. Cannulated Screws with a diameter of 2.0 mm are manly in use for foot and hand surgery.

    The aap Cannulated Screw 2.0 consists of:
    • Cannulated Screw 2.0, Long thread
    • Cannulated Screw 2.0, Short thread
    • Washer
    • Set of Instruments Cannulated Screws

    AI/ML Overview

    The provided text describes a 510(k) premarket notification for the "aap Cannulated Screw 2.0". This is a medical device application for orthopedic screws, and the "acceptance criteria" and "study" refer to mechanical and performance testing against established standards for such devices, rather than a clinical study with human or animal subjects or an AI/ML context.

    Here's a breakdown of the requested information based on the provided text, focusing on the mechanical testing described:

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

    Acceptance Criteria (Standard)Reported Device Performance
    ASTM F543-07 relevant requirementsThe Screws fulfill the relevant requirements of ASTM F543-07 and pre-defined acceptance criteria and intended uses.

    2. Sample size used for the test set and the data provenance

    • Sample Size: Not specified in the provided text. The document states "Non-clinical tests have been performed" and "mechanical testing to show the substantial equivalence," but does not detail the number of screws tested.
    • Data Provenance: The tests are non-clinical (mechanical tests) and were performed by the manufacturer, aap Implantate AG. The country of origin for the data would be Germany, where the sponsor is located, or a testing facility commissioned by them. The data is prospective in the sense that the tests were conducted specifically for this submission.

    3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts

    This question is not applicable to this type of submission. "Ground truth" in this context refers to a standard of mechanical performance, not expert consensus on medical images or diagnoses. The "ground truth" is defined by the ASTM F543-07 standard.

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

    This question is not applicable. Adjudication methods like 2+1 or 3+1 are used for establishing ground truth in clinical or imaging studies where expert consensus is needed. For mechanical testing against a standard, the results are objectively measured and compared to the standard's specifications.

    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 is not applicable. The device is a physical orthopedic screw, not an AI/ML algorithm or imaging device that would involve human readers or AI assistance in interpretation.

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

    This is not applicable as the device is a physical medical implant, not an algorithm.

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

    The "ground truth" for the non-clinical tests is the specified mechanical performance requirements outlined in the ASTM F543-07 standard.

    8. The sample size for the training set

    This is not applicable. There is no AI/ML algorithm involved, and therefore no training set.

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

    This is not applicable as there is no AI/ML algorithm or training set.

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