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510(k) Data Aggregation

    K Number
    K102326
    Date Cleared
    2010-11-15

    (90 days)

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

    PARCUS 3.5MM PEEK CF PUSH-IN SUTURE ANCHOR

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

    The Parcus 3.5mm PEEK CF Push-In Suture Anchors are indicated for attachment of soft tissue to bone. This product is intended for the following indications:
    Shoulder: Rotator Cuff Repair, Acromioclavicular Separation Repair, Bankart Lesion Repair, Biceps Tenodesis, Capsular Shift or Capsulolabral Reconstruction, Deltoid Repair, SLAP Lesion Repair.
    Knee: Medial Collateral Ligament Repair, Lateral Collateral Ligament Repair, Posterior Oblique Ligament Repair, Extra Capsular Reconstruction, Iliotibial Band Tenodesis, Patellar Ligament and Tendon Avulsion Repair.
    Foot/Ankle: Lateral Stabilization, Medial Stabilization, Midfoot Reconstruction, Achilles Tendon Repair, Hallux Valgus Reconstruction, Metatarsal Ligament Repair.
    Elbow: Tennis Elbow Repair, Biceps Tendon Reattachment.
    Hand/Wrist: Scapholunate Ligament Reconstruction, Ulnar or Radial Collateral Ligament Reconstruction, TFCC

    Device Description

    The Parcus 3.5mm PEEK CF Push-In Suture Anchors are tapered fasteners with barbs for use in attachment of soft tissue to bone. The devices are made from Carbon Fiber Reinforced Polyetheretherketone (PEEK CF). The Push-In Suture Anchors are provided sterile.

    AI/ML Overview

    The provided document is a 510(k) summary for the Parcus 3.5mm PEEK CF Push-In Suture Anchor. It describes the device, its intended use, and argues for its substantial equivalence to predicate devices based on performance data. However, it does not describe an AI/ML-driven device or study. Therefore, the following information cannot be extracted from the provided text.

    Acceptance Criteria and Study for an AI/ML Device:

    Since the provided document pertains to a physical medical device (suture anchor) and not an AI/ML-driven device, the following categories are not applicable. The document describes a "Summary Performance Data" section which details a mechanical pull-out strength test for the suture anchor, not an AI model's performance.

    1. Table of acceptance criteria and the reported device performance:

      • The document states: "The Parcus 3.5mm PEEK CF Push-In Suture Anchors were placed in prepared holes and the pull out strength was measured. Test results were compared to the results for the Parcus V-LoX PEEK CF Suture Anchors as well as the Smith & Nephew BioRaptor 2.9 and demonstrated substantial equivalence."
      • It does not provide specific acceptance criteria values (e.g., minimum pull-out strength in Newtons) nor the precise numerical performance results of the Parcus anchor or the predicate devices. It only states that the results demonstrated "substantial equivalence."
    2. Sample size used for the test set and the data provenance: Not applicable for an AI/ML device study. For the mechanical test, the sample size is not explicitly stated. The nature of the data is mechanical test results, not clinical or image data.

    3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts: Not applicable, as this is not an AI/ML device requiring expert ground truth for classification or detection.

    4. Adjudication method 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: Not applicable.

    6. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done: Not applicable.

    7. The type of ground truth used (expert consensus, pathology, outcomes data, etc.): Not applicable for an AI/ML device. For the mechanical test, the "ground truth" would be the direct measurement of pull-out strength in a lab setting.

    8. The sample size for the training set: Not applicable.

    9. How the ground truth for the training set was established: Not applicable.

    In summary, the provided text describes a 510(k) submission for a physical medical device (suture anchor) and does not contain information related to an AI/ML device or its performance study against specific acceptance criteria relevant to AI/ML.

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