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510(k) Data Aggregation

    K Number
    K072813
    Manufacturer
    Date Cleared
    2007-12-28

    (88 days)

    Product Code
    Regulation Number
    868.1400
    Reference & Predicate Devices
    Predicate For
    AI/MLSaMDIVD (In Vitro Diagnostic)TherapeuticDiagnosticis PCCP AuthorizedThirdpartyExpeditedreview
    Intended Use

    The EMMA Emergency Capnometer Monitor measures, displays and monitors carbon dioxide concentration and respiratory rate during anesthesia, recovery and respiratory care. It may be used in the operating suite, intensive care unit, patient room, clinic, emergency medicine and emergency transport settings for adult, pediatric and infant patients.

    The EMMA Emergency Capnometer Analyzer measures and displays carbon dioxide concentration and respiratory rate during anesthesia, recovery and respiratory care. It may be used in the operating suite, intensive care unit, patient room, clinic, emergency medicine and emergency transport settings for adult, pediatric and infant patients.

    Device Description

    The EMMA Emergency Capnometer is a miniature mainstream infrared gas analysis bench with an integrated user interface. The complete carbon dioxide analyzer is contained within a transducer that is attached to the breathing circuit via the EMMA Airway Adapter.

    AI/ML Overview

    The provided text describes the EMMA Emergency Capnometer and states that testing was done in direct comparison to predicates throughout the operating range using calibrated gas samples and legally marketed anesthesia and ventilation devices. The conclusion was that the device demonstrated performance, safety, and effectiveness equivalent or superior to its predicates in all characteristics. However, the document does not explicitly detail specific acceptance criteria or provide a table of reported device performance against those criteria.

    Given the information provided, I can only address some of your questions.

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

    The provided text does not contain a specific table of acceptance criteria with corresponding reported device performance values. It only generally states that the device "demonstrated performance, safety and effectiveness equivalent or superior to its predicates in all characteristics."

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

    The text mentions "calibrated gas samples" but does not specify the sample size used for the test set. It also does not specify the data provenance (e.g., country of origin, retrospective or prospective).

    3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts (e.g. radiologist with 10 years of experience)

    This is not applicable as the study involved "calibrated gas samples and legally marketed anesthesia and ventilation devices" rather than human-interpreted data requiring expert consensus for ground truth.

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

    This is not applicable, as there's no indication of human adjudication for the device performance testing.

    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

    A multi-reader multi-case (MRMC) comparative effectiveness study was not conducted. This device is a capnometer, not an AI-assisted diagnostic tool for human readers.

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

    The testing described ("Testing in direct comparison to predicates throughout the operating range was conducted using calibrated gas samples and legally marketed anesthesia and ventilation devices") inherently represents a standalone performance evaluation of the EMMA Emergency Capnometer. There is no mention of a human-in-the-loop component for the performance assessment itself.

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

    The ground truth was established by "calibrated gas samples" and the performance of "legally marketed anesthesia and ventilation devices" (presumably as a reference standard for comparison with the device's measurements).

    8. The sample size for the training set

    The device is a hardware capnometer, not based on a machine learning algorithm that requires a training set. Therefore, a training set is not applicable or mentioned.

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

    As there is no training set for this type of device, this question is not applicable.

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