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510(k) Data Aggregation

    K Number
    K193646
    Date Cleared
    2020-12-04

    (340 days)

    Product Code
    Regulation Number
    868.5430
    Reference & Predicate Devices
    Why did this record match?
    Applicant Name (Manufacturer) :

    Anesthetic Gas Reclamation, Inc.

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

    The Dynamic Gas Scavenging System is intended to be used for the scavenging of waste anesthesia machines during the provision of general anesthesia to adults and children.

    Device Description

    The Dynamic Gas Scavenging System 2 (DGSS-2) is a waste anesthetic scavenging interface placed between the individual anesthetic workstation and the waste gas evacuation vacuum system in a surgical care facility. Through a sensor and solenoid combination, it allows waste gas exhaust flow to the waste gas vacuum line only in the presence of waste anesthetic gas, and interrupts all exhaust flow when no waste gas is present. The system effectively prevents both positive and negative pressure on the patient breathing circuit, and it is usable over a wide range of anesthetic gas flows. It is designed for use in conjunction with low-flow (

    AI/ML Overview

    The provided text does not describe a study involving an AI/software device that meets specific acceptance criteria related to accuracy, sensitivity, or specificity in a medical imaging context. Instead, it details a 510(k) submission for a medical device called the "Dynamic Gas Scavenging System 2 (DGSS-2)", which is used to scavenge waste anesthetic gases.

    This device is not an AI/software product, nor does the document describe any performance study involving human readers, ground truth establishment by experts, or the use of training and test sets as would be typical for an AI/ML medical device. The "Non-Clinical Performance Data" section on page 9 refers to engineering and quality assurance measures and performance testing against standards, not clinical performance in terms of diagnostic accuracy or reader improvement.

    Therefore, I cannot provide the requested information for acceptance criteria and a study proving device performance as outlined in your prompt, because the provided document relates to a physical medical device and its engineering validation, not an AI/software product with the types of performance metrics you specified.

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