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510(k) Data Aggregation

    K Number
    K133561
    Device Name
    VENACURE EVLT NEVERTOUCH PROCEDURE KIT, VENACURE EVLT TRE' SHEATH
    Manufacturer
    ANGIODYNAMICS, INC.
    Date Cleared
    2013-12-19

    (29 days)

    Product Code
    GEX
    Regulation Number
    878.4810
    Type
    Special
    Panel
    General & Plastic Surgery
    Reference & Predicate Devices
    K102796,K100199
    Predicate For
    N/A
    AI/MLSaMDIVD (In Vitro Diagnostic)TherapeuticDiagnosticis PCCP AuthorizedThirdpartyExpeditedreview
    Intended Use

    The VenaCure EVLT Tre' Sheath and VenaCure EVLT NeverTouch Procedure Kits are indicated for endovascular coagulation of the Great Saphenous Vein (GSV) in patients with superficial vein reflux, for the treatment of varicose veins and varicosities associated with superficial reflux of the Great Saphenous Vein (GSV), and for the treatment of incompetence and reflux of superficial veins of the lower extremity.

    Device Description

    The VenaCure EVLT Tre' Sheath is a 4F sheath used during endovascular venous laser treatment procedures. The sheath is used as a conduit for placing a laser fiber. The product will be offered in 25, 45, 65 and 90cm lengths. The VenaCure EVLT Tre' Sheath will be provided both as a standalone product and also packaged with a variety of procedural accessories.

    AI/ML Overview

    This document is a 510(k) Summary for a medical device called the "VenaCure EVLT Tre' Sheath and VenaCure EVLT NeverTouch Procedure Kit." It's a submission to the FDA for market clearance, not an AI performance study. Therefore, most of the requested information regarding acceptance criteria for AI devices and associated studies is not applicable.

    However, I can extract the information that is present in the document which relates to the device's performance assessment for its 510(k) clearance.

    Here's a breakdown of the relevant information:

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

    The document does not specify quantitative acceptance criteria with numerical targets. Instead, it describes "non-clinical performance testing" comparing the device to a predicate device. The implied acceptance criterion for these tests is "substantially equivalent" to the predicate, meaning the device performs similarly and meets the same safety and effectiveness standards.

    Acceptance Criteria Category (Implied)Reported Device Performance (Summary)
    Mechanical/Physical PropertiesThe proposed device has similar materials, design, components, and technical characteristics as the predicate device. The results of non-clinical performance testing demonstrate substantial equivalence. Specific tests include:
    Visual InspectionPassed/Met standards (implied by "substantially equivalent")
    Sheath / Dilator Interface (Length and Force to Withdraw)Passed/Met standards (implied by "substantially equivalent")
    Depth Mark SpacingPassed/Met standards (implied by "substantially equivalent")
    Surface Friction TestingPassed/Met standards (implied by "substantially equivalent")
    Static Pressure TestingPassed/Met standards (implied by "substantially equivalent")
    Luer Lock Fitting TestingPassed/Met standards (implied by "substantially equivalent")
    Tensile Test Hub JointsPassed/Met standards (implied by "substantially equivalent")
    Needle TensilePassed/Met standards (implied by "substantially equivalent")
    Functional Performance
    Fiber OutputPassed/Met standards (implied by "substantially equivalent")
    Biocompatibility
    Biocompatibility per ISO 10993-1Passed/Met standards (implied by "substantially equivalent")

    Regarding the AI-specific questions, these are not applicable to this document as it describes a physical medical device, not an AI system.

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

      • Not Applicable: This document describes non-clinical performance testing of a physical medical device, not an AI algorithm. There is no "test set" in the context of data for an AI model.

    2. 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: As above, this is not an AI study.

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

      • Not Applicable: As above, this is not an AI study.

    4. 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: As above, this is not an AI study.

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

      • Not Applicable: As above, this is not an AI study.

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

      • Not Applicable in the AI context: For this physical device, the "ground truth" (or reference standard) is established by recognized engineering and biocompatibility standards (e.g., ISO 10993-1) and the performance of the predicate device.

    7. The sample size for the training set

      • Not Applicable: This is not an AI study.

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

      • Not Applicable: This is not an AI study.
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