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510(k) Data Aggregation

    K Number
    K082215
    Date Cleared
    2008-11-03

    (89 days)

    Product Code
    Regulation Number
    888.3030
    Reference & Predicate Devices
    AI/MLSaMDIVD (In Vitro Diagnostic)TherapeuticDiagnosticis PCCP AuthorizedThirdpartyExpeditedreview
    Intended Use

    The Smith & Nephew OSTEORAPTOR Suture Anchor is intended for the reattachment of soft tissue to bone for the following indications: Elbow, Wrist, and Hand (Biceps tendon reattachment, Ulnar or radial collateral ligament reconstructions, Lateral epicylitis repair), Foot and Ankle (Hallux valgus repairs, Medial or lateral instability repairs/reconstructions, Achilles tendon repairs/reconstructions, Midfoot reconstructions, Metatarsal ligament/tendon repairs/reconstructions, Bunionectomy), Hip (Hip capsule repair, Acetabular labrum reattachment), Knee (Extra-capsular repairs: Medial collateral ligament, Lateral collateral ligament, Posterior oblique ligament, Patellar realignment and tendon repairs, Vastus medialis obliquous advancement, Iliotibial band tenodesis), Shoulder (Capsular stabilization, Bankart repair, Anterior shoulder instability, SLAP lesion repairs, Capsular shift or capsulolabral reconstructions, Acromioclavicular separation repairs, Deltoid repairs, Rotator cuff tear repairs, Biceps tenodesis).

    Device Description

    The device consists of a suture anchor with attached non-absorbable suture(s) preassembled to an insertion device. This device is provided sterile, for single use only.

    AI/ML Overview

    The document provided is a 510(k) summary for a medical device called the OSTEORAPTOR® Suture Anchor. This is a premarket notification to the FDA for a device that is not an AI/ML powered diagnostic device. Therefore, the questions related to AI/ML specific aspects like training data, test set, ground truth adjudication, MRMC studies, etc., do not apply to this document.

    The document indicates that the device's performance was evaluated by demonstrating "substantial equivalence" to legally marketed predicate devices. This is a regulatory pathway for medical devices that are similar to existing ones.

    Here's an attempt to answer the relevant questions based on the provided text, while explicitly stating where information is not applicable or unavailable for a non-AI/ML device.

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

    For a traditional medical device like a suture anchor, "acceptance criteria" and "reported device performance" are typically defined by demonstrating substantial equivalence to predicate devices through various established engineering and biocompatibility tests, rather than diagnostic performance metrics. The document states:

    Intended Use / Fundamental Scientific TechnologyAcceptance Criteria (Implicit)Reported Device Performance (Claimed)
    Intended UseSubstantially equivalent to predicate devices (BIORAPTOR 2.9 Anchor (K053344) and BIORAPTOR 2.3 PK Anchor (K071586)).The Smith & Nephew OSTEORAPTOR Suture Anchor is intended for the reattachment of soft tissue to bone for the same indications as the predicate devices (Elbow, Wrist, Hand, Foot, Ankle, Hip, Knee, Shoulder). The FDA's letter states approval "for the indications for use stated in the enclosure."
    Fundamental Scientific TechnologySubstantially equivalent to predicate devices."The proposed and predicate anchors are similar in design, operate on the same principles, have the same indications and intended use, and exhibit similar fixation properties."
    Performance TestingDemonstrates substantial equivalence in insertion and fixation properties to predicate devices."The performance testing conducted demonstrates that the insertion and fixation properties of the OSTEORAPTOR Anchor are substantially equivalent to the predicate devices." (Specific numerical criteria or test results are not provided in this summary, but would be expected in the full 510(k) submission).

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

    This information is not applicable in the context of an AI/ML diagnostic device's test set. For physical medical devices, performance testing involves engineering tests, biocompatibility tests, and potentially cadaveric or animal studies. The 510(k) summary provided does not detail the sample sizes or provenance for these types of tests, only stating that "performance testing was conducted."

    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 is not applicable as this is not an AI/ML powered diagnostic device requiring ground truth established by experts.

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

    This is not applicable as this is not an AI/ML powered diagnostic device.

    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 as this is not an AI/ML powered device. MRMC studies are used for evaluating diagnostic performance of AI or AI-assisted diagnostic tools.

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

    This is not applicable as this is not an AI/ML powered device.

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

    This is not applicable for a physical medical device. Ground truth refers to the verified correct answer in diagnostic tasks, which is not relevant for a suture anchor's performance assessment. Instead, the "truth" for this device would be established by physical measurements, mechanical properties testing, and biocompatibility standards.

    8. The sample size for the training set

    This is not applicable as this is not an AI/ML powered device. "Training set" refers to data used to train AI models.

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

    This is not applicable as this is not an AI/ML powered device.

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