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510(k) Data Aggregation

    K Number
    K191366

    Validate with FDA (Live)

    Date Cleared
    2019-09-06

    (107 days)

    Product Code
    Regulation Number
    876.1500
    Reference & Predicate Devices
    Predicate For
    AI/MLSaMDIVD (In Vitro Diagnostic)TherapeuticDiagnosticis PCCP AuthorizedThirdpartyExpeditedreview
    Intended Use

    The Vacutore® Air/Water Bottle Tubing (Model GAR025, GAR076) is to connect an air/CO2 source, a sterile water source (water bottle), and an endoscope to supply air/CO2 and water during gastrointestinal endoscopic procedures. It is a 24-hour multi-patient use device.

    Device Description

    The Vacutore® Air/Water Bottle Tubing is intended for 24-hour multi-patient use. Air/water bottle tubing is supplied in sterile. The Vacutore® Air/Water Bottle Tubing is manufactured for use in conjunction with sterile water bottle, and together with Olympus 160 and Pentax 90 series endoscopes. The air/water bottle tubing is individually packed in sealed package, sold as a sterile device. The air/water bottle tubing is designed to be attached to the air/water port of the endoscopes to provide irrigation through the air/water channel to the distal end of endoscope.

    AI/ML Overview

    The provided document is a 510(k) Premarket Notification for a medical device called "Vacutore® Air/Water Bottle Tubing." This type of submission focuses on demonstrating substantial equivalence to a predicate device, rather than proving novel effectiveness through a comprehensive study with specific acceptance criteria related to a diagnostic output or algorithm performance.

    Therefore, the typical metrics for acceptance criteria and study descriptions (like sensitivity, specificity, types of ground truth, number of experts, MRMC studies, effect sizes, and separate test/training sets with explicit ground truth establishment) are generally not applicable in the context of this device and submission type.

    Instead, the acceptance criteria here relate to the performance, safety, and functional equivalence of the tubing device compared to an existing predicate.

    Here's an analysis based on the information provided, addressing the questions as much as possible for this type of device:

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

    The document does not explicitly state numerical "acceptance criteria" and "reported device performance" in the way one would for an AI diagnostic device (e.g., "sensitivity > 90%"). Instead, it lists tests performed and states that these tests support substantial equivalence. The "performance" is implicitly "met all tests successfully" to be considered substantially equivalent.

    Acceptance Criterion (Implicit)Reported Device Performance (Implicit)
    Assembling IntegrityPassed
    Endoscope CompatibilityPassed
    Compatibility with BottlePassed
    Two-Way Valve IntegrityPassed
    Flow Clamp TestPassed
    Water Flow TestPassed
    Back Flow Performance TestPassed
    Sterility (SAL of 10⁻⁶)Passed (Validated EO sterilization)
    EO residuals (ANSI/AAMI/ISO 10993-7)Below maximum levels
    Shelf Life (3 years)Passed (Verified by accelerated aging, seal strength, dye penetration, microbial barrier, vacuum leak, sterility tests)
    Biocompatibility (ISO 10993-1)Passed (Acute Systemic Toxicity, In Vitro Cytotoxicity, Skin sensitization, Irritation tests showed biocompatibility)
    Barrier Integrity & Simulated Use Testing (24-hour multi-patient use)Passed (Verified back-flow prevention and 24-hour multi-patient use)

    2. Sample size used for the test set and the data provenance (e.g. country of origin of the data, retrospective or prospective)

    The document does not specify a "sample size" in terms of number of patients or images, as this is a tubing device. The testing was performed on "Smartdata samples from initial production lots." The provenance of these samples would be the manufacturer, Smartdata Suzhou Co., Ltd., in China. These would be considered prospective in the sense they are new production samples being tested.

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

    This is not applicable. The device is a piece of medical tubing, not a diagnostic or AI-driven decision support system that requires expert interpretation for ground truth. The "ground truth" here is physical performance (e.g., does it leak? does it flow water correctly? is it sterile?).

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

    This is not applicable. Adjudication methods are used to establish ground truth in studies involving human interpretation or clinical outcomes. For bench testing of a physical device, the results are typically objectively measured and do not require expert adjudication in this manner.

    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

    No. An MRMC study is relevant for diagnostic or AI-assisted interpretation, where human readers evaluate cases with and without AI assistance. This device is a piece of tubing used in endoscopic procedures, not an AI diagnostic tool.

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

    No. This refers to the performance of an algorithm without human input, which is not relevant for this device. The testing described is "standalone" in the sense that the tubing itself was tested for its physical and functional properties.

    7. The type of ground truth used (expert consensus, pathology, outcomes data, etc)

    The "ground truth" for this device's performance is based on objective measurement of physical properties and adherence to established standards. Examples include:

    • Physical integrity (no leaks, secure connections)
    • Flow rates (water flow test)
    • Sterility (Sterility Assurance Level, EO residuals)
    • Material compatibility (biocompatibility tests)
    • Durability (shelf life accelerated aging)
    • Functional performance (back-flow prevention, compatibility with endoscopes/bottles).

    8. The sample size for the training set

    Not applicable. This device does not involve a "training set" in the context of machine learning or AI models.

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

    Not applicable, as there is no training set.

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