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510(k) Data Aggregation

    K Number
    K101114
    Manufacturer
    Date Cleared
    2011-07-26

    (461 days)

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

    OTC: For minor wounds, minor ulcerations, minor burns, minor abraded skin, and minor irritated areas.

    Professional: Intended in the management of:

    • diabetic foot ulcers; .
    • . leg ulcers (venous stasis ulcers, arterial ulcers and leg ulcers of mixed etiology);
    • pressure ulcers/sores (partial and full thickness); .
    • 1st and 2nd degree partial thickness burns; ●
    • grafted and donor sites and traumatic and surgical wounds. ●
    Device Description

    Activon Tube ™ Sterile 100% Manuka Honey is a wound care dressing for use in moist wound management. The Activon Tube TM Sterile 100% Manuka Honey is offered as a 0.99 oz (2.8 g) twist off cap squeeze tube for one-time use .

    AI/ML Overview

    The provided text describes a 510(k) submission for a wound care dressing, focusing on its substantial equivalence to predicate devices, rather than an AI/ML medical device. Therefore, a direct response to the requested information about acceptance criteria, study details, and AI performance metrics is not applicable.

    Here's why and what can be extracted:

    • Device Type: The device is "Activon Tube ™ Sterile 100% Manuka Honey," a traditional wound dressing. It is not an AI/ML device.
    • Regulatory Pathway: The submission is a 510(k), which demonstrates substantial equivalence to a legally marketed predicate device. This pathway typically relies on comparison of technological characteristics and performance data (e.g., biocompatibility) to prove safety and effectiveness, rather than a clinical trial demonstrating AI performance.

    Extracted Information (relevant to the document's content):

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

      • The document does not specify "acceptance criteria" in the format typically associated with AI/ML device performance metrics (e.g., sensitivity, specificity, AUC).
      • Instead, performance is demonstrated by biocompatibility testing (cytotoxicity, sensitization, and irritation), which showed the dressing is safe for its intended use. This implicitly acts as an "acceptance criterion" for this class of device.
      • The device also demonstrates performance through substantial equivalence to predicate devices with established safety and effectiveness for similar indications.
    2. Sample size used for the test set and the data provenance (e.g., country of origin of the data, retrospective or prospective):

      • Not applicable as this is not an AI/ML study. Biocompatibility testing typically involves in vitro and/or animal studies, the "sample size" of which is not detailed here.
    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 as this is not an AI/ML study requiring expert ground truth for interpretation.
    4. Adjudication method (e.g., 2+1, 3+1, none) for the test set:

      • Not applicable as this is not an AI/ML study.
    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 as 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 as this is not an AI/ML device.
    7. The type of ground truth used (expert consensus, pathology, outcomes data, etc):

      • For biocompatibility, the "ground truth" would be the observed biological response to the device materials as compared to established safety endpoints.
    8. The sample size for the training set:

      • Not applicable as this is not an AI/ML device.
    9. How the ground truth for the training set was established:

      • Not applicable as this is not an AI/ML device.

    In summary, the provided document describes the regulatory submission for a non-AI/ML medical device (wound dressing). The "performance data" focuses on demonstrating biological safety (biocompatibility) and technological equivalence to predicate devices, rather than the statistical performance metrics typically associated with AI/ML software.

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