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510(k) Data Aggregation

    K Number
    K203794
    Date Cleared
    2021-02-01

    (35 days)

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

    HEALIX Ti Dual Threaded Suture Anchor with DYNATAPE Suture

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

    The HEALIX Ti™ Dual Threaded Suture Anchor is intended for soft-tissue-to-bone fixation with postoperative immobilization.

    Shoulder: Rotator Cuff Repair, Bankart Repair, Biceps Tenodesis, Acromioclavicular Separation Repair, Deltoid Repair, Capsular Shift or Capsulolabral Reconstruction;

    Foot/Ankle: Lateral Stabilization, Medial Stabilization, Achilles Tendon Repair;

    Knee: Medial Collateral Ligament Repair, Lateral Collateral Ligament Repair, Posterior Oblique Ligament Repair, Iliotibial Band Tenodesis, Patellar Tendon repair and secondary fixation in ACL/PCL reconstruction repair; Elbow: Biceps Tendon Reattachment, Ulnar or Radial Collateral Ligament Reconstruction.

    Device Description

    The proposed HEALIX TiTM Dual Threaded Suture Anchor with DYNATAPETM Suture is a line extension to the currently marketed HEALIX TiTM Anchor family. The HEALIX Ti Anchor is a non-absorbable dual threaded suture anchor comprised of Titanium material. The threaded anchor comes preloaded on a disposable inserter assembly and is intended for fixation of one strand of #2 DYNACORD Suture and one strand of 2.5 mm DYNATAPE Suture to bone. The HEALIX TiTM Dual Threaded Suture Anchor with DYNATAPETM Suture is provided sterile via Ethylene Oxide (EO) sterilization and is for single use only.

    AI/ML Overview

    This is a 510(k) premarket notification for a medical device (HEALIX Ti™ Dual Threaded Suture Anchor with DYNATAPE™ Suture), not a traditional AI/ML software as a medical device (SaMD) submission. Therefore, much of the requested information (like acceptance criteria for AI performance, sample sizes for AI training/test sets, expert ground truth establishment, MRMC studies, and standalone AI performance) is not applicable or present in this document.

    The document focuses on demonstrating substantial equivalence to predicate devices through material, design, and performance testing, typical for hardware medical devices.

    However, I can extract the relevant "acceptance criteria" and "study results" related to the device's mechanical performance:

    1. Table of Acceptance Criteria and Reported Device Performance (Non-AI related)

    Acceptance Criteria CategorySpecific Test/EvaluationAcceptance Criteria (Implied)Reported Device PerformanceComments
    Mechanical PerformanceFixation strength following cyclic loadingSufficient strength to perform intended soft-tissue-to-bone fixationDemonstrated "sufficient" strengthThis is implied, as the conclusion states the device is "suitable for their intended use." Specific numeric criteria and results are not provided in this summary.
    Knot tensile strengthSufficient strength for binding tissuesDemonstrated "sufficient" strengthImplied as above.
    Suture approximation testingEffective tissue approximationDemonstrated "effective" approximationImplied as above.
    SterilizationSterilization validation (Ethylene Oxide)Sterility Assurance Level (SAL) of 1 x 10-6Validated to SAL of 1 x 10-6 per ANSI/AAMI/ISO 11135:2014Meets the specified standard.
    Biocompatibility/SafetyEO residualsCompliant levels of ethylene oxide residualsTested per AAMI/ANSI/ISO 10993-7:2008 and found compliantMeets the specified standard.
    Non-pyrogenicityNon-pyrogenicDetermined to be non-pyrogenic per ANSI/AAMI ST-72:2011, USP, and EP using Bacterial Endotoxin Testing (BET) methodMeets the specified standards.
    Substantial EquivalenceSimilar indications for use, technological characteristics, and performance to predicatesDevice characteristics and performance are comparable to the identified predicate devices, demonstrating safe and effective use.Demonstrated substantial equivalence to K183279 and K200949 based on similarities in indications for use, technological characteristics, and performance.This is the overarching "acceptance criterion" for a 510(k) submission.

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

    • This document does not specify a "test set" in the context of an AI/ML device. The "Non-clinical Testing" section refers to verification activities performed on the proposed device and its predicates.
    • No details on sample sizes (e.g., number of anchors tested) for the mechanical or biocompatibility tests are provided in this summary.
    • Data provenance (e.g., country of origin, retrospective/prospective) is not applicable or specified for these types of engineering and laboratory tests.

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

    • Not applicable. This device does not involve expert ground truth for a diagnostic or prognostic AI algorithm. The "ground truth" for its performance is derived from standardized engineering and laboratory testing methods.

    4. Adjudication method for the test set:

    • Not applicable. There is no human reading or diagnostic task requiring adjudication.

    5. If a multi-reader multi-case (MRMC) comparative effectiveness study was done:

    • No. This is not an AI/ML diagnostic or assistive device.

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

    • Not applicable. This is a hardware medical device; it does not have a standalone algorithm component.

    7. The type of ground truth used:

    • For mechanical performance tests (fixation strength, tensile strength, approximation): The "ground truth" is defined by the physical properties and performance measured against engineering specifications and industry standards.
    • For sterilization and biocompatibility: The "ground truth" is established by adherence to validated international standards (e.g., ISO 11135, ISO 10993-7, ANSI/AAMI ST-72, USP, EP) and laboratory testing demonstrating compliance.

    8. The sample size for the training set:

    • Not applicable. There is no "training set" in the context of an AI/ML algorithm.

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

    • Not applicable.
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