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510(k) Data Aggregation

    K Number
    K063059
    Manufacturer
    Date Cleared
    2007-04-19

    (196 days)

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

    Rx: Sorbact® Wound Dressings are intended for use in the management of moderate to heavily exudating partial to full thickness wounds (including clean, colonized, contaminated or infected wounds) and to bind hydrophobic microbes The dressing is indicated for post-operative wounds, trauma wounds, shallow cavity wounds, fistulas, pressure ulcers, diabetic ulcers, and venous ulcers.
    OTC: Sorbact® Wound Dressings are intended for use in the management of draining minor wounds and to attract and bind water repelling germs. The dressing may be used on minor scrapes, cuts, sores and burns.

    Device Description

    Sorbact Wound Dressings are sterile bandages that attract and capture water-repelling (hydrophobic) microorganisms. The dressings are coated with DACC (dialky) carbamoyl chloride), a hydrophobic (water-repelling) fatty ester acid that binds to and reduces the overall concentration of hydrophobic microbes in a wound each time the dressing is changed. Available Sorbact products include adsorbent dressings, compresses, ribbon gauze tamponades, round swabs and surgical dressings.

    AI/ML Overview

    The provided text describes the Sorbact® Wound Dressing and its substantial equivalence to predicate devices, but it does not contain acceptance criteria or detailed study results that prove the device meets specific acceptance criteria.

    The document states:

    • "Sorbact® wound dressings have been shown in studies, including in vitro and clinical tests, to be safe and effective for their intended uses." (Page 4, Section V)

    However, it lacks the specific data points needed to answer your questions within the context of acceptance criteria and proven performance. This document is a 510(k) summary, which typically focuses on demonstrating substantial equivalence rather than presenting comprehensive study data with acceptance criteria.

    Therefore, I cannot populate the table or provide detailed answers to most of your questions based solely on the provided text.

    Here's a breakdown of what can be inferred from the provided text and what is missing:


    1. Table of Acceptance Criteria and Reported Device Performance

    Cannot be provided. The document states that in vitro and clinical tests were conducted to show safety and effectiveness, but it does not specify any quantitative acceptance criteria (e.g., "bacterial reduction must be >X%") or the actual performance metrics achieved in those tests.


    2. Sample Size Used for the Test Set and Data Provenance

    Cannot be provided. The document mentions "clinical tests" but does not provide any details about the sample size (number of patients/wounds), study design, or data provenance (e.g., country of origin, retrospective/prospective nature).


    3. Number of Experts Used to Establish Ground Truth and Qualifications

    Cannot be provided. The document does not describe the establishment of a ground truth for a test set, nor does it mention any expert involvement in such a process. This kind of detail is typically relevant for studies involving subjective assessments (e.g., image-based diagnostics) which is not the primary focus of a wound dressing's efficacy where clinical outcome is key.


    4. Adjudication Method for the Test Set

    Cannot be provided. As there's no mention of a test set with subjective assessments by experts, there's no description of an adjudication method.


    5. Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study

    Cannot be provided. The document does not describe an MRMC study or any scenario where human readers would improve with or without AI assistance, as this device is a wound dressing, not an AI diagnostic tool.


    6. Standalone Algorithm Performance

    Cannot be provided. This question is irrelevant as the Sorbact® Wound Dressing is a physical medical device, not an algorithm.


    7. Type of Ground Truth Used

    Cannot be provided in detail. For a medical device like a wound dressing, the "ground truth" for demonstrating safety and effectiveness would typically be clinical outcomes (e.g., wound healing rates, reduction in infection, absence of adverse events), and potentially microbiological data for its antimicrobial claims. However, the document does not specify how this ground truth was established or measured in the "clinical tests."


    8. Sample Size for the Training Set

    Cannot be provided. This question is irrelevant as the Sorbact® Wound Dressing is a physical medical device, not a machine learning model that requires a training set.


    9. How the Ground Truth for the Training Set Was Established

    Cannot be provided. This question is irrelevant for the same reason as point 8.

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