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510(k) Data Aggregation

    K Number
    K053388
    Date Cleared
    2006-04-04

    (120 days)

    Product Code
    Regulation Number
    868.5895
    Reference & Predicate Devices
    Why did this record match?
    Device Name :

    MODEL 840 VENTILATOR WITH PROPORTIONAL ASSIST VENTILATION PLUS SOFTWARE OPTION

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

    The Puritan Bennett 840 ventilator with Proportional Assist Ventilation® Plus (PAV+) software option is intended for use in spontaneously breathing adult patients whose ventilator ideal body weight (IBW) is at least 25.0 kg. Patients must be intubated with either endotracheal or tracheostomy tubes of internal diameter of 6.0 mm to 10.0 mm. Patients must have satisfactory neural-ventilatory coupling, and stable, sustainable inspiratory drive.

    PAV+ is intended for use in hospitals and hospital-type facilities.

    Device Description

    Proportional Assist Ventilation Plus is a software option for the Puritan Bennett 840 Ventilator that includes a spontaneous breath type called, Proportional Assist. PAV+ is designed to assist the spontaneous breathing patient with an active neural drive. Proportional Assist amplifies the patient's inspiratory effort. A control function allows the clinician to specify an amplification setting.

    AI/ML Overview

    The provided text describes a 510(k) submission for the Puritan Bennett 840 Ventilator with Proportional Assist Ventilation® Plus (PAV+) software option, which is a continuous ventilator.

    Here's an analysis of the acceptance criteria and the study that proves the device meets them, based on the provided text:

    1. Table of Acceptance Criteria and Reported Device Performance

    The provided text does not explicitly state quantitative acceptance criteria or specific performance metrics that were established as targets for the PAV+ software. However, it indicates a qualitative acceptance criterion: "substantial equivalence" to legally marketed predicate devices.

    Acceptance Criteria (Qualitative)Reported Device Performance
    Substantial equivalence to legally marketed predicate devices (Puritan Bennett 840 Ventilator with Volume Ventilation Plus and Dräger EvitaXL with SmartCare/PS) in terms of safety and effectiveness.Performance data (system level, controls, clinical simulation, hospital setting) "demonstrates substantial equivalence" in technological characteristics and safety/effectiveness.

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

    The document mentions "Clinical simulation testing" and "Evaluations... conducted in a hospital setting" but does not provide specific sample sizes for these test sets. The provenance of the data (country of origin, retrospective or prospective) is also not specified.

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

    The document states that "Clinical simulation testing was conducted to evaluate the PAV+ software in the hands of respiratory therapists." This implies that respiratory therapists were the users and evaluators, acting as a form of "expert" group. However, the exact number of these respiratory therapists and their specific qualifications (e.g., years of experience) are not provided. It's also unclear if they established a formal "ground truth" or simply provided feedback and assessments of the software's performance.

    4. Adjudication Method for the Test Set

    The document does not specify an adjudication method (e.g., 2+1, 3+1, none) for the test set. It broadly refers to "evaluations."

    5. If a Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study Was Done, and the Effect Size of How Much Human Readers Improve with AI vs Without AI Assistance

    No MRMC comparative effectiveness study is mentioned. The device is a ventilator software option, not an imaging analysis tool that typically involves "readers" in the context of MRMC studies. The focus is on the software's performance and its interaction with a human operator (respiratory therapist) rather than improving human "reading" performance. Therefore, an "effect size of how much human readers improve with AI vs without AI assistance" is not applicable in this context.

    6. If a Standalone (i.e., algorithm only without human-in-the-loop performance) Was Done

    The document states, "Performance data includes results from testing at the system level and conducting testing on controls." This suggests some level of standalone testing of the algorithm's components or the overall system without direct human interaction at all times. However, the exact nature and extent of this standalone testing are not detailed. The "clinical simulation testing" and "evaluations... in a hospital setting" clearly involved human-in-the-loop performance.

    7. The Type of Ground Truth Used

    The document doesn't explicitly define a "ground truth" in the sense of a gold standard (like pathology or outcome data) for the PAV+ software's performance. Instead, the "ground truth" appears to be implicitly established by:

    • Comparison to predicate devices: The functionality and performance of the PAV+ software were assessed against the known characteristics and performance of the Puritan Bennett 840 Ventilator with Volume Ventilation Plus and the Dräger EvitaXL with SmartCare/PS.
    • Clinical judgment/experience of respiratory therapists during simulation and hospital evaluations.
    • Measured characteristics of the patient (pulmonary compliance and total pulmonary resistance) as inputs for the PAV+'s proportional pressure augmentation, implying that the algorithm's calculations and subsequent actions were verifiable.

    8. The Sample Size for the Training Set

    The document does not provide any information regarding a training set sample size. This submission is for a medical device software, and while software development typically involves training and testing, the regulatory filing focuses on the final performance demonstration. The term "training set" is usually associated with machine learning models, and while PAV+ involves complex algorithms, it's not explicitly framed as an AI/ML product requiring a distinct "training set" description in this 2006 K05.

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

    As no training set is explicitly mentioned or detailed, the method for establishing its ground truth is also not provided.

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