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510(k) Data Aggregation

    K Number
    K063488
    Device Name
    MAXO2 CU
    Manufacturer
    Date Cleared
    2007-02-22

    (97 days)

    Product Code
    Regulation Number
    868.1720
    Reference & Predicate Devices
    Why did this record match?
    Device Name :

    MAXO2 CU

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

    The MaxO2 CU is a continuous use monitor of oxygen concentration in a patient breathing environment. It may be provided with an oxygen concentration dilution method which could be of a flowmeter, manifold or venturi design, which can deliver a set or adjustable FiO2 oxygen concentrations and flow rates to the patient. It is not intended for use with life supporting systems.

    Device Description

    The MaxO2 CU is a combination of a continuous use oxygen monitor and a venturi oxygen dilution system in one device. An analogous device could be assembled by attaching a wall mount oxygen flow meter to a commercially available venturi and attaching the venturity a standard in-line oxygen analyzer. The MaxO2 CU offers this set-up to the clinician in one package. There are two models, one with adjustable flow and adjustable FiO2. The other has fixed flow and adjustable FiO. The flow adjustment is accomplished by adjusting the flow of oxygen through the venturi orifice. The adjustable oxygen % is accomplished by adjusting the flow of oxygen into the region surrounding the venturi orifice. This oxygen is drawn into the venturi stream in place of room air, increasing oxygen content in the mixture. The oxygen analyzer electronics, sensor, and programming are identical to the MaxQ+ predicate K040484.

    AI/ML Overview

    Here's an analysis of the provided text regarding the MaxO2 CU device's acceptance criteria and documented performance.

    1. Table of Acceptance Criteria and Reported Device Performance

    AttributeAcceptance Criteria (Stated)Reported Device Performance
    Display range0-100% oxygen0-100% oxygen
    Display Resolution0.1% oxygen0.1% oxygen
    Response TimeNot explicitly stated as "acceptance criteria" but
                                 implied performance goal for the device. The
                                 predicate device may have set a benchmark.
                                | 90% of final value in ~ 15 seconds @ 23C |
    

    | Accuracy | Not explicitly stated as "acceptance criteria" but
    implied performance goal for the device. The
    predicate device may have set a benchmark.
    | + 3% full scale |
    | Linearity error | Not explicitly stated as "acceptance criteria" but
    implied performance goal for the device. The
    predicate device may have set a benchmark.
    | 900,000 % oxygen hours |

    Note: The document lists "Device Attributes" with specific values. While not explicitly termed "acceptance criteria," for a 510(k) submission, these values represent the performance the manufacturer claims to meet and which the FDA reviews for substantial equivalence to predicate devices. The absence of specific "acceptance criteria" numbers often means the device is being compared to the predicate's established performance without a formal, new testing standard being defined for this submission beyond maintaining functional equivalence.

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

    The provided document does not contain information about a specific test set, its sample size, or data provenance (e.g., country of origin, retrospective/prospective). The submission refers to performance specifications (e.g., accuracy, response time) but does not detail the studies conducted to verify these specifications for this specific device. This is common in 510(k) submissions where substantial equivalence is demonstrated primarily through comparison to predicate devices, and underlying performance data might be referenced from internal testing or previous submissions for the predicate.

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

    The document does not mention any experts or ground truth establishment relevant to a clinical or performance test set. The device is an oxygen analyzer, and its performance characteristics (accuracy, linearity) would typically be verified against calibrated reference gases or standards, not through expert consensus on medical imagery or patient outcomes.

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

    As there is no mention of a clinical or performance test set involving human interpretation, there is no adjudication method described. This device measures gas concentration, a quantitative physical parameter.

    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 MRMC comparative effectiveness study was done or is mentioned. This device is an oxygen analyzer, not an AI diagnostic tool that assists human readers.

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

    The document does not describe a standalone algorithm performance study. The device itself is a standalone physical instrument for measuring oxygen concentration. The performance metrics listed (accuracy, drift, response time) are inherent to the device's function, not an algorithm in the AI sense.

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

    The "ground truth" for verifying the performance attributes of an oxygen analyzer (like Display Range, Accuracy, Linearity error, Drift) would typically be based on calibrated reference gases with known oxygen concentrations, or highly accurate laboratory instruments. The document does not explicitly state the methodology for establishing this ground truth, but it would be a metrological standard, not clinical expert consensus or pathology.

    8. The sample size for the training set

    The document does not refer to a training set. This device is an electro-mechanical oxygen analyzer; it does not utilize machine learning or AI models that require a training set.

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

    As there is no training set, there is no discussion of how its ground truth was established.

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