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510(k) Data Aggregation

    K Number
    K110471
    Manufacturer
    Date Cleared
    2011-10-07

    (231 days)

    Product Code
    Regulation Number
    868.5905
    Reference & Predicate Devices
    Why did this record match?
    Device Name :

    BABI PLUS INFANT NASAL CANNULA SYSTEM

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

    Single patient use device intended for use with neonates, infants and children under 10 Kg requiring a nasal prong interface during intermittent or continuous gas flow therapy in the hospital critical care unit.

    Device Description

    Single patient use nasal cannula offered in 8 different sizes which have been specifically designed for patents ≤ 10 Kg. The device includes a short length of 10 mm corrugated tubing allowing connection to a variety of devices. The device also provides a means to monitor delivered pressure at the nasal prong.

    AI/ML Overview

    Here's an analysis of the provided text regarding the acceptance criteria and study for the Babi.Plus Infant Nasal Cannula System:

    The information provided describes a 510(k) premarket notification for a medical device (Babi.Plus Infant Nasal Cannula System), emphasizing its substantial equivalence to a predicate device. The core of the "study" proving acceptance criteria here is a bench testing and dimensional analysis comparison to a legally marketed predicate device, rather than a clinical trial with human subjects.

    Here's a breakdown of the requested information based on the provided text:


    Acceptance Criteria and Device Performance

    The acceptance criteria are implicitly defined by demonstrating "substantially equivalent performance" to the predicate device. The performance characteristics compared are "Resistance to gas flow in the inspiratory circuit" and "Resistance to gas flow in the expiratory circuit."

    1. Table of Acceptance Criteria and Reported Device Performance:

    Acceptance Criterion (Implicit)Predicate Device Performance (Reported)Proposed Device Performance (Reported)
    Resistance to gas flow in the inspiratory circuit:
    Gas Flow (L/min) 10
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    K Number
    K093716
    Manufacturer
    Date Cleared
    2010-05-13

    (162 days)

    Product Code
    Regulation Number
    868.5905
    Reference & Predicate Devices
    Why did this record match?
    Device Name :

    BABI PLUS INFANT NASAL CANNULA SYSTEM

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

    Single patient use device intended for use with neonates, infants and children under 10 Kg requiring a nasal prong interface during intermittent or continuous gas flow therapy in the hospital critical care unit.

    Device Description

    Single patient use nasal cannula offered in 8 different sizes which have been specifically designed for patents ≤ 10 Kg. The device includes a short length of 10 mm corrugated tubing allowing connection to a variety of devices. Pre-conditioned gas (heat, moisture, flow and oxygen concentration) is provided to the device's inspiratory circuit. The gas is channeled to the nasal cannula for inhalation. Expired gas is channeled away from the nasal cannula and eventually is vented to the surrounding environment. The device also includes a pressure monitor nasal prong (proximal airway) pressure.

    AI/ML Overview

    The provided text describes the Babi*Plus Nasal Cannula system and its substantial equivalence to a predicate device, focusing on technological characteristics and bench testing. However, it does not include information about acceptance criteria or specific studies detailing device performance in the way typically expected for AI/ML medical devices. The document is a 510(k) summary for a physical medical device (nasal cannula), not a software or AI product.

    Therefore, many of the requested details, particularly those related to AI/ML development (e.g., sample size for test/training sets, ground truth methodology, expert adjudication, MRMC studies, standalone performance), are not applicable or present in this document.

    Here's a breakdown of the available information in relation to your request:

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

    The document does not explicitly state "acceptance criteria" in a quantitative, threshold-based manner as might be seen for an AI diagnostic. Instead, it focuses on demonstrating substantial equivalence to a predicate device. The performance is reported in terms of bench testing for specific characteristics.

    Acceptance Criteria (Implied by Substantial Equivalence Goal)Reported Device Performance (Bench Testing)
    Substantially equivalent dimensions and calculated dead space (Vps) within the nasal prong.A dimension analysis of the Babi*Plus Nasal Cannula and the predicate was performed which demonstrated substantially equivalent dimensions as well as calculated dead space (Vps) within the nasal prong.
    Substantially equivalent resistance to gas flow in the inspiratory circuit at 1-12 LPM.Testing of resistance to gas flow in the inspiratory circuit of the Babi*Plus Nasal Cannula and predicate device at gas flows of 1 to 12 LPM showed substantial equivalency.
    Substantially equivalent resistance to gas flow in the expiratory circuit at 1-12 LPM.Testing of resistance to gas flow in the expiratory circuit of the Babi*Plus Nasal Cannula and predicate device at gas flows of 1 to 12 LPM showed substantial equivalency.
    Accurate measurement of nasal prong (proximal airway) pressure at various pressures and gas flows.Testing was performed to show the accuracy of measuring nasal prong (proximal airway) pressure at various pressures and gas flows. (The document states "Testing to show the accuracy," implying successful results for this criterion for substantial equivalence, but specific accuracy metrics are not provided).

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

    This information is not applicable as the described tests are bench tests on physical devices (nasal cannulas), not data-driven tests on a "test set" in the context of AI/ML or clinical data. There is no mention of human subjects, data provenance, or retrospective/prospective studies.

    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 information is not applicable. Ground truth, expert consensus, and expert qualifications are relevant for studies involving human interpretation or complex diagnostic tasks, typically with AI/ML. The evaluation here is based on physical measurements and engineering principles for a medical device.

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

    This information is not applicable as there is no "test set" requiring adjudication by experts.

    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:

    This information is not applicable. This is a physical medical device (nasal cannula), not an AI-assisted diagnostic tool. Therefore, MRMC studies and human reader improvement with AI are irrelevant to this submission.

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

    This information is not applicable. This is a physical medical device, not an algorithm.

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

    The "ground truth" for the bench tests would be the accurate physical measurements obtained using standard methods and calibrated equipment (e.g., flow meters, pressure transducers). It's based on scientific principles and engineering measurements rather than clinical expert consensus or pathology.

    8. The sample size for the training set:

    This information is not applicable as there is no "training set" in the context of an AI/ML device.

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

    This information is not applicable as there is no "training set."

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