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510(k) Data Aggregation

    K Number
    K173918
    Date Cleared
    2018-08-17

    (238 days)

    Product Code
    Regulation Number
    868.5690
    Reference & Predicate Devices
    Why did this record match?
    Reference Devices :

    K173825, K150173

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

    VersaPAP* is indicated for the treatment and prevention of atelectasis. VersaPAP* also has the ability to provide supplemental oxygen when used with compressed oxygen. The VersaPAP* device is for patients (ages 5 years and above) who are capable of following directions for Positive Airway in a hospital environment. The VersaPAP* device is a single patient, multiple use device intended to be used under the supervision of a healthcare professional.

    Device Description

    The VersaPAP* device is a hand held respiratory therapy device that creates a positive airway pressure. The VersaPAP* device is intended to be used by pediatric (ages 5 years and above) and adult patients in the hospital environment, under the supervision of a healthcare professional. The VersaPAP* device is a single patient use device and may be used for two treatments per day for 7 days. A manometer gauge is included to monitor airway pressure while operating the VersaPAP* device. The VersaPAP* device consists of seven components: a mouthpiece, the VersaPAP* backpiece (includes 3 components: the baffle, body and end cap), a manometer adapter, a manometer gauge, and oxygen tubing.

    AI/ML Overview

    The provided text is a 510(k) summary for the VersaPAP Positive Airway Pressure (PAP) Device. It describes the device, its intended use, and its comparison to a predicate device (EzPAP). However, it does not contain any information about acceptance criteria or specific study data to prove the device meets performance metrics.

    The document explicitly states:

    • "*Performance testing included comparative testing against the predicate device using representative patient generated breathing patterns. Testing confirmed that the VersaPAP device is substantially equivalent to the predicate.**" (Page 6, Section 9.1)
    • "Not applicable, the determination of substantial equivalence is not based on Clinical Performance data." (Page 8, Section 10)

    This type of 510(k) submission generally relies on demonstrating substantial equivalence to a legally marketed predicate device rather than conducting extensive clinical performance studies with predefined acceptance criteria and human expert adjudication, especially for devices like PAP devices where safety and effectiveness are often established through engineering and comparative testing.

    Therefore, I cannot populate the requested table or answer most of the questions because the information is not present in the provided text. The document clearly indicates that performance demonstration was done through comparative engineering testing against a predicate device, not through a study involving human readers, ground truth consensus, or clinical performance metrics in the way your questions imply for AI/diagnostic devices.

    Here's what can be inferred or explicitly stated from the document:

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

    • No explicit acceptance criteria or reported device performance metrics are provided in the text. The submission states that "Performance testing included comparative testing against the predicate device using representative patient generated breathing patterns. Testing confirmed that the VersaPAP* device is substantially equivalent to the predicate." This implies that the device performed similarly to the predicate, but no quantitative acceptance criteria (e.g., specific pressure ranges, flow rates) or detailed results from this comparative testing are included in this summary.

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

    • This information is not provided. The "test set" in this context would likely refer to the parameters or conditions under which the comparative engineering tests were performed (e.g., range of simulated breathing patterns), not a clinical data set.

    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):

    • Not applicable / not provided. This device is a mechanical Positive Airway Pressure device, not an image-based diagnostic or AI system requiring expert ground truth for a test set. The performance testing was comparative engineering testing.

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

    • Not applicable / not provided. This is not a study requiring adjudication of expert interpretations.

    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, an MRMC study was not done. This device is not an AI-assisted diagnostic tool.

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

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

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

    • Not applicable. The "ground truth" for this device's performance would be engineering specifications and the established performance characteristics of the predicate device, against which it was compared using simulated breathing patterns.

    8. The sample size for the training set:

    • Not applicable. This document describes a traditional 510(k) for a physical device, not an AI or machine learning model that requires a training set.

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

    • Not applicable.

    In summary, the provided document focuses on demonstrating substantial equivalence through general performance testing (likely bench testing) and material biocompatibility against a predicate device, rather than providing detailed clinical study data with predefined acceptance criteria as would be expected for a novel diagnostic or AI-driven system.

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