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510(k) Data Aggregation

    K Number
    K060296
    Date Cleared
    2006-03-31

    (53 days)

    Product Code
    Regulation Number
    876.5820
    Reference & Predicate Devices
    Predicate For
    AI/MLSaMDIVD (In Vitro Diagnostic)TherapeuticDiagnosticis PCCP AuthorizedThirdpartyExpeditedreview
    Intended Use

    The NxStage Dialysate Preparation Module is an optional accessory to the NxStage System One that prepares dialysate for use during hemodialysis, as prescribed by the physician.

    Device Description

    The NxStage Dialysate Preparation Module is an optional accessory to the NxStage System One that pre-treats and purifies water that mixes with concentrate to produce dialysate meeting the requirements of the ANSI/AAMI Standards, RD52:2004 and The dialysate is to be used with the NxStage System One during RD62:2001. hemodialysis treatments.

    AI/ML Overview

    The provided text describes a Special 510(k) Device Modification for the NxStage Dialysate Preparation Module, focusing on its substantial equivalence to a predicate device. It does not contain information about acceptance criteria, device performance, or a study that uses a test set, ground truth, or expert review in the way a typical AI/ML medical device submission would.

    Therefore, the following information is based on the provided text, and many sections will indicate that the information is "Not applicable" or "Not provided" for this type of device modification.


    Acceptance Criteria and Device Performance

    Acceptance CriteriaReported Device Performance
    Substantial Equivalence to Predicate DeviceThe modified NxStage Dialysate Preparation Module was compared to the baseline device (K043436) and found to be substantially equivalent based on device indications for use, comparison of descriptive and technological characteristics, and design control certification.
    Meeting Design SpecificationsDesign validation testing was performed to ensure that the modified device meets design specifications.
    Compliance with ANSI/AAMI StandardsThe device produces dialysate meeting the requirements of ANSI/AAMI Standards, RD52:2004 and RD62:2001.
    Compliance with Design Control RequirementsCertification of compliance to 21 CFR 820.30 Design Control requirements was provided.
    Intended UseThe device meets the minimum requirements considered acceptable for its intended use (preparing dialysate for hemodialysis with the NxStage System One).

    Study Details

    1. Sample size used for the test set and the data provenance: Not applicable. This was a Special 510(k) Device Modification focusing on design validation and substantial equivalence, not a clinical study on a test set in the context of an AI/ML device.
    2. Number of experts used to establish the ground truth for the test set and the qualifications of those experts: Not applicable. Ground truth as typically defined for AI/ML performance evaluation (e.g., expert consensus on medical images) was not established for this type of device modification.
    3. Adjudication method (e.g., 2+1, 3+1, none) for the test set: Not applicable.
    4. 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: Not applicable. This device is a Dialysate Preparation Module, not an AI-assisted diagnostic or interpretative device that would involve human readers.
    5. If a standalone (i.e., algorithm only without human-in-the-loop performance) was done: Not applicable. This device is a medical device, not an AI algorithm. Its performance is evaluated based on its physical and functional characteristics to prepare dialysate.
    6. The type of ground truth used (expert consensus, pathology, outcomes data, etc.): The "ground truth" for this device's performance would be the physical and chemical properties of the dialysate it produces, validated against established standards (ANSI/AAMI RD52:2004 and RD62:2001) and its design specifications. It is based on objective measurements and engineering principles, not expert consensus on medical images or pathology.
    7. The sample size for the training set: Not applicable. This device does not use machine learning, so there is no "training set."
    8. How the ground truth for the training set was established: Not applicable.
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