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510(k) Data Aggregation

    K Number
    K150939
    Device Name
    Ensizor Endoscopic Scissors
    Manufacturer
    SLATER ENDOSCOPY, LLC
    Date Cleared
    2015-06-08

    (62 days)

    Product Code
    OCZ
    Regulation Number
    876.1500
    Type
    Traditional
    Panel
    Gastroenterology/Urology
    Reference & Predicate Devices
    K133736,K141058
    Predicate For
    K180134,K242923
    Why did this record match?
    Reference Devices :

    K133736

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

    Slater Endoscopy Ensizor™ Endoscopic Scissors are designed to cut and dissect tissue and sutures during all flexible endoscopic procedures.

    Device Description

    The above referenced Endoscopic Scissors are sterile, single use, non-electrocautery devices for soft tissue dissection and the cutting of sutures during flexible endoscopic procedures. The devices are compatible with flexible endoscopes with a minimum channel diameter of 2.8 mm. The device cuts and dissects tissue and suture materials during all flexible endoscopic procedures. The device consists principally of an actuation handle and a flexible shaft body terminating in a pair of cutting scissors. The scissor blades function as standard scissors for mechanical cutting of sutures and tissue.

    AI/ML Overview

    I am sorry, but the provided text does not contain the detailed information necessary to answer your request about the acceptance criteria and study proving device performance as it relates to AI/ML devices. The document describes a 510(k) submission for "Ensizor Endoscopic Scissors," which are mechanical, non-AI medical devices.

    Therefore, I cannot extract:

    1. A table of acceptance criteria and reported device performance related to an AI/ML device.
    2. Sample size used for the test set or data provenance for an AI/ML study.
    3. Number of experts or their qualifications for establishing ground truth in an AI/ML context.
    4. Adjudication method for an AI/ML test set.
    5. MRMC comparative effectiveness study results (effect size of human readers with/without AI assistance).
    6. Standalone (algorithm-only) performance results.
    7. Type of ground truth used (e.g., pathology, outcomes data) for an AI/ML model.
    8. Sample size for the training set of an AI/ML model.
    9. How ground truth for the training set was established for an AI/ML model.

    The document discusses non-clinical performance data for the endoscopic scissors, including:

    • Operation in Tortuosity: Ensuring the device can open and close when the distal shaft is formed into a 20 cm diameter circle.
    • Sample Cutting: Cutting various suture and polyethylene materials at least 10 times.
    • Comparative Testing to US Endoscopy Suture Cutter: Functional testing in straight and tortuous pathways, and simulation testing to grasp and cut various sutures.

    The table provided in the document summarizes acceptance criteria and performance for these mechanical tests, not AI/ML performance.

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