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510(k) Data Aggregation

    K Number
    K041235
    Date Cleared
    2004-06-04

    (24 days)

    Product Code
    Regulation Number
    870.1025
    Reference & Predicate Devices
    Why did this record match?
    Reference Devices :

    K014159, K021778, K032858, K040304, K040183, K040357

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

    Indicated for use by health care professionals monitoring the physiological parameters whenever there is a need for monitoring, recording and alarming of multiple physiological parameters of adults, pediatrics and neonates in hospital environment and during transport within hospital environments. Models MP20, MP30, MP40 and MP50 are additionally intended for use in transport situations within hospital environments. ST Segment monitoring is restricted to adult patients only. The transcutaneous gas measurement (tcp0₂ / tcpCO₂) is restricted to neonatal patients only.

    Device Description

    The Philips MP20, MP30, MP40, MP50, MP60, MP70, and MP90 IntelliVue Patient Monitors.

    AI/ML Overview

    The Philips MP20, MP30, MP40, MP50, MP60, MP70, and MP90 IntelliVue Patient Monitors underwent verification, validation, and testing activities to establish their performance, functionality, and reliability characteristics. The study that proves the device meets the acceptance criteria is described as follows:

    1. Table of Acceptance Criteria and Reported Device Performance:

    Acceptance CriteriaReported Device Performance
    PerformanceMeets all reliability requirements and performance claims.
    FunctionalityMeets specifications cleared for the predicate device.
    ReliabilityMeets all reliability requirements and performance claims.
    SafetyMeets safety requirements based on hazard analysis.
    System-levelTest results showed substantial equivalence to the predicate device.

    Note: The 510(k) summary explicitly states that "Pass/Fail criteria were based on the specifications cleared for the predicate device." However, the exact quantitative metrics for these specifications are not provided in the summary.

    2. Sample Size Used for the Test Set and Data Provenance:

    The document does not explicitly state the sample size used for the test set or the data provenance (e.g., country of origin, retrospective or prospective). It generally refers to "system level tests, performance tests, and safety testing."

    3. Number of Experts Used to Establish Ground Truth for the Test Set and Qualifications of Experts:

    This information is not provided in the 510(k) summary. The testing appears to be based on engineering and predefined specifications rather than expert adjudicated ground truth on clinical data.

    4. Adjudication Method for the Test Set:

    This information is not provided. The testing described appears to be based on objective pass/fail criteria derived from predicate device specifications, rather than a clinical adjudication process.

    5. If a Multi-Reader Multi-Case (MRMC) Comparative Effectiveness study was done:

    No, a Multi-Reader Multi-Case (MRMC) comparative effectiveness study was not explicitly mentioned or performed. The submission focuses on substantial equivalence to predicate devices through technical testing.

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

    The testing described appears to be standalone performance testing of the device's hardware and software against predefined specifications. The summary does not describe any human-in-the-loop performance evaluation in the context of this submission.

    7. The type of Ground Truth Used:

    The "ground truth" for the device's performance was based on the "specifications cleared for the predicate device." This implies a comparison to established technical and performance requirements of previously approved devices, rather than clinical outcomes data or pathology.

    8. The Sample Size for the Training Set:

    This information is not applicable or provided. The submission describes a medical device update (software release and new models) and does not suggest the use of machine learning algorithms that would require a distinct "training set" for model development.

    9. How the Ground Truth for the Training Set Was Established:

    This information is not applicable or provided, as the submission does not detail the use of a training set for machine learning. The device's performance validation is based on adherence to the specifications of predicate devices.

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