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510(k) Data Aggregation

    K Number
    K060165
    Manufacturer
    Date Cleared
    2006-09-01

    (221 days)

    Product Code
    Regulation Number
    878.5000
    Reference & Predicate Devices
    Why did this record match?
    Device Name :

    AXYAFLEX POLYESTER SUTURE

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

    AxyaFlex™ polyester suture is indicated for use in general soft tissue approximation and/or ligation, including use in cardiovascular, ophthalmic and neurological procedures.

    Device Description

    AxyaFlex™ polyester suture is a nonabsorbable, braided, sterile, surgical suture composed of poly(ethylene terephthalate co-isophthalate). It is prepared from fibers of high molecular weight, long-chain, linear polyesters having recurrent aromatic rings as an integral component. AxyaFlex™ sutures are braided for optimal handling properties.

    AI/ML Overview

    The provided text is a 510(k) summary for a surgical suture and does not contain information about the acceptance criteria or a study that proves the device meets specific performance criteria in the context of an AI/ML-based device. Instead, it focuses on demonstrating substantial equivalence to predicate devices through physical and chemical properties and biocompatibility.

    Therefore, many of the requested categories for AI/ML device evaluation are not applicable or cannot be extracted from this document.

    Here's an attempt to answer the questions based on the provided text, while noting where information is missing or not relevant to AI/ML devices:

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

    Acceptance Criteria (from USP & FDA Guidance)Reported Device Performance
    Suture Diameter requirementsSatisfied USP requirements
    Suture Length requirementsSatisfied USP requirements
    Knot Tensile Strength requirementsSatisfied USP requirements
    BiocompatibilityEquivalent to predicate polyester material
    Chemical AnalysesEquivalent to predicate polyester material
    Sterilization ProcessEquivalent to predicate suture manufacturers' process

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

    • Sample Size for Test Set: Not specified. The document mentions "summaries of studies" but does not detail the sample sizes for the tests conducted to evaluate suture diameter, length, and knot tensile strength.
    • Data Provenance: Not specified.

    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. This is a medical device (suture), not an AI/ML diagnostic or prognostic tool requiring expert-established ground truth for performance evaluation in the clinical sense. The "ground truth" here would be objective measurements against established standards (USP).

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

    • Not applicable. (See #3)

    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 not an AI/ML device.

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

    • Not applicable. This is not an AI/ML device.

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

    • The "ground truth" implicitly used for the physical and mechanical properties (diameter, length, knot tensile strength) would be the United States Pharmacopeia (USP) standards and FDA Guidance Document entitled "Class II Special Controls Guidance Document: Surgical Sutures." For biocompatibility and chemical analyses, the ground truth would be established scientific and regulatory benchmarks for safety and equivalence to predicate materials.

    8. The sample size for the training set

    • Not applicable. This is not an AI/ML device with a training set.

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

    • Not applicable. This is not an AI/ML device.
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