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510(k) Data Aggregation

    K Number
    K061220
    Device Name
    URGOTUL AG
    Manufacturer
    Date Cleared
    2006-07-27

    (87 days)

    Product Code
    Regulation Number
    N/A
    Reference & Predicate Devices
    Why did this record match?
    Reference Devices :

    K013525, K001519

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

    The barrier functions of Urgotul® Ag Antimicrobial Wound Dressing may help reduce infection in light to moderately exudative partial and full thickness wounds, including diabetic ulcers, first and second degree burns, decubitus ulcers, venous stasis ulcers, and graft and donor sites.

    Device Description

    Urgotul® Ag wound dressing is a sterile, antimicrobial hydrocolloid wound contact dressing with silver. Urgotul® Ag wound dressing is non-occlusive and non-adhesive for painless removal. Urgotul® Ag is composed of a polyester mesh impregnated with a matrix of carboxymethylcellulose hydrocolloid particles, cohesion polymers and Vaseline containing silver.

    AI/ML Overview

    The provided text [0-3] does not contain information about acceptance criteria or a study proving the device meets acceptance criteria. This document is a 510(k) summary for a medical device (Urgotul® Ag Antimicrobial Wound Dressing) and primarily focuses on device description, indications for use, and a substantial equivalence determination to predicate devices. It does not include details on performance studies with specific statistical metrics that would define acceptance criteria or demonstrate compliance.

    Therefore, I cannot fulfill your request for:

    1. A table of acceptance criteria and reported device performance.
    2. Sample sizes or data provenance for a test set.
    3. Number and qualifications of experts for ground truth.
    4. Adjudication method for a test set.
    5. MRMC comparative effectiveness study results.
    6. Standalone algorithm performance.
    7. Type of ground truth used.
    8. Sample size for the training set.
    9. How ground truth for the training set was established.
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