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510(k) Data Aggregation

    K Number
    K083354
    Date Cleared
    2009-07-20

    (249 days)

    Product Code
    Regulation Number
    878.4370
    Reference & Predicate Devices
    N/A
    Why did this record match?
    Device Name :

    FLORASEAL, MODEL FS350D

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

    Flora Seal™ Microbial Sealant is intended for use after topical operative skin preparations, with standard surgical draping, and prior to a surgical incision. The product is used to reduce the risk of the skin flora contamination throughout a surgical procedure.

    Device Description

    Flora Seal Microbial Sealant is a film forming, cyanoacrylate based microbial sealant provided in a ready to use applicator. Each applicator consists of a thermoformed blister tray with a heat sealed lid with an attached applicator sponge tip. This applicator tray with sponge tip is contained in an outer Tyvek pouch.

    AI/ML Overview

    The provided text describes the FloraSeal Microbial Sealant and its substantial equivalence to the predicate device, InteguSeal. Since this is a 510(k) summary for a medical device (microbial sealant) rather than an AI/ML powered device, many of the requested categories in the prompt relate specifically to AI/ML studies and are not applicable here.

    Here's an analysis based on the provided text:

    FloraSeal Microbial Sealant

    1. Table of Acceptance Criteria and Reported Device Performance:

    Acceptance Criteria (Implied)Reported Device Performance
    Reduce microbial colonization by a significant percentage and duration.Reduced microbial colonization by 99.9% within 15 minutes of application and maintained this reduction for 24 hours.
    Performance equal or better than predicate device (Integuseal) in bench tests.FloraSeal provided results that were equal to or better than Integuseal in tests for wound closure strength, film integrity over time, flexibility properties (FloraSeal significantly better), MVTR, setting time, surface coverage, hydrostatic pressure, and water impact penetration.

    2. Sample size used for the test set and the data provenance:

    • Sample Size: The clinical test involved "volunteer subjects." The exact number of subjects is not specified.
    • Data Provenance: The study was a clinical test on human subjects. The country of origin is not specified, but given the FDA 510(k) submission, it is likely that the data was generated in the US or under US regulatory standards. It was a prospective study, as subjects participated in a washout period prior to evaluation for stabilization of skin bacterial flora.

    3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts:

    • Not Applicable. This device is a microbial sealant, and its performance (microbial reduction) would be assessed through microbiological laboratory analysis and clinical observation, not by human experts establishing ground truth for image interpretation or similar AI/ML tasks.

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

    • Not Applicable. As above, this concept is not relevant for the evaluation of a microbial sealant.

    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 device.

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

    • Not Applicable. This is not an AI/ML device. The device (sealant) performs its function directly.

    7. The type of ground truth used:

    • For microbial reduction: Microbiological assays/measurements (e.g., bacterial counts from skin samples) to quantify the reduction in microbial colonization.
    • For bench tests: Engineering and material science measurements for various properties like wound closure strength, film integrity, flexibility, MVTR, setting time, surface coverage, hydrostatic pressure, and water impact penetration.

    8. The sample size for the training set:

    • Not Applicable. This is not an AI/ML device, so there is no "training set" in the context of machine learning.

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

    • Not Applicable. As there is no training set for an AI/ML model, this question is irrelevant.
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