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510(k) Data Aggregation

    K Number
    K203132

    Validate with FDA (Live)

    Date Cleared
    2021-04-15

    (178 days)

    Product Code
    Regulation Number
    876.5015
    Reference & Predicate Devices
    Predicate For
    N/A
    AI/MLSaMDIVD (In Vitro Diagnostic)TherapeuticDiagnosticis PCCP AuthorizedThirdpartyExpeditedreview
    Intended Use

    The AXIOS™ Stent and Electrocautery-Enhanced Delivery System is indicated for use to facilitate transgastric or transduodenal endoscopic drainage of symptomatic pancreatic pseudocysts ≥ 6 cm in size, that are adherent to the gastric or bowel wall and are free of solid debris. The stent is intended for implantation up to 60 davs and should be removed upon confirmation of pseudocyst resolution.

    Device Description

    The AXIOS Stent is a flexible, MR conditional, fully-covered self-expanding braided nitinol stent, which comes preloaded into the delivery system. The AXIOS stent is designed with two flanges on each end to prevent migration and to enable tissue plane apposition and a "saddle" in between the flanges to span the tissue implant distance.

    The AXIOS Electrocautery-Enhanced Delivery System consists of a catheter and an integrated handle with manual controls for positioning and deploving the AXIOS Stent. The AXIOS Electrocautery-Enhanced Delivery System is designed to be used in the gastrointestinal tract with commercially available echoendoscopes with a 3.7 mm diameter or larger working channel and is compatible with commercially available 0.035-inch insulated endoscopic guidewires.

    The Electrocautery-Enhanced Delivery System connects with an off-the-shelf electrosurgical unit or generator that is compliant to IEC 60601-1-2 and IEC 60601-2-2.

    The AXIOS Stent and Electrocautery-Enhanced Delivery System is provided sterile, disposable and intended for single use.

    AI/ML Overview

    This FDA 510(k) summary describes a medical device, the AXIOS Stent and Electrocautery-Enhanced Delivery System, and its performance. However, it does not involve an AI/ML algorithm, and therefore the acceptance criteria and study information related to AI/ML performance metrics (such as effect size for human readers with AI assistance, type of ground truth, training set size, etc.) are not applicable here.

    The document focuses on demonstrating substantial equivalence to a predicate device (K181905) through engineering performance data (bench testing) rather than clinical study data involving AI/ML.

    Here's a breakdown of the available information based on your request, with an emphasis on what is not present due to the nature of this device submission:

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

    The document provides a table summarizing the types of bench tests performed and their results. The "acceptance criteria" are implied by the "Pass" result for each test, indicating that the device met the pre-defined product specifications for these engineering parameters. Specific numerical acceptance criteria values are not provided, only the pass/fail outcome.

    Test ItemReported Result (Pass/Fail)
    AXIOS Stent
    Deployed Stent Saddle LengthPass
    Deployed Stent Saddle Outer DiameterPass
    Deployed Stent Flange WidthPass
    Stent Pull-out ForcePass
    Stent (Saddle) Radial Strength - in compression & expansionPass
    Deployment ForcePass
    Implant Anchor Function- Retention (tensile)Pass
    Magnetic Resonance TestingPass
    Fatigue TestingPass
    AXIOS 9 Fr. Electrocautery-Enhanced Delivery System
    Delivery System Working LengthPass
    Catheter ExtensionPass
    Nose Lock Hold ForcePass
    Slider Lock Hold ForcePass
    Nose Lock CyclingPass
    Slider Lock CyclingPass
    Distal Pusher Catheter to Distal Nose Joint StrengthPass
    Pusher Catheter to Hypotube Joint StrengthPass
    Outer Sheath to Hypotube Joint StrengthPass
    Pusher Hypotube to Handle Joint StrengthPass
    Outer Sheath Hypotube to Handle Joint StrengthPass
    Distal Pusher to Proximal Pusher Catheter Joint StrengthPass
    Outer Sheath to Handle Torque StrengthPass
    Luer to Nose Joint StrengthPass
    Tracking ForcePass

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

    • Sample Size: Not specified for the bench tests. For medical devices, bench testing typically involves a sufficient number of samples to ensure statistical confidence in the results, but the exact N is not disclosed in this summary.
    • Data Provenance: Not applicable as this relates to engineering bench testing of physical device components, not clinical data sets.

    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 device is not an AI/ML diagnostic tool requiring expert interpretation for ground truth establishment. The "ground truth" for the performance tests are engineering specifications verified through physical measurement and functional testing.

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

    Not applicable. This is not a clinical study involving human interpretation or adjudication of cases.

    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 powered device, and no MRMC study was conducted or mentioned.

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

    Not applicable. There is no algorithm to test in a standalone configuration.

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

    The "ground truth" for these tests are the pre-defined product specifications and engineering requirements for the device's physical and functional characteristics. This is established through engineering design, material science, and manufacturing standards.

    8. The sample size for the training set

    Not applicable. This is not an AI/ML device, so there is no training set.

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

    Not applicable. As there is no AI/ML component, there is no training set or associated ground truth establishment process.

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