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510(k) Data Aggregation

    K Number
    K171331
    Date Cleared
    2017-08-24

    (108 days)

    Product Code
    Regulation Number
    876.5860
    Reference & Predicate Devices
    Predicate For
    N/A
    AI/MLSaMDIVD (In Vitro Diagnostic)TherapeuticDiagnosticis PCCP AuthorizedThirdpartyExpeditedreview
    Intended Use

    The NxStage System One is indicated for the treatment of acute and chronic renal failure or fluid overload using hemofiltration, hemodialysis, and/or ultrafiltration, in an acute or chronic care facility. The System is also indicated for home hemodialysis, including home nocturnal hemodialysis and solo home hemodialysis during waking hours. All treatments must be administered under physician's prescription, and must be performed by a trained and qualified person, considered to be competent in the use of this device by the prescribing physician.

    Device Description

    The NxStage System One is comprised of the NxStage Cycler, an electromechanical control unit; the NxStage Cartridge, a sterile, single-use extracorporeal blood and fluid management circuit (with or without a pre-attached high permeability filter) that mounts integrally within the NxStage Cycler. The combined system is designed to deliver hemofiltration, hemodialysis and/or ultrafiltration in an acute or chronic care facility. The NxStage System One is also indicated for home hemodialysis, including home nocturnal hemodialysis.

    AI/ML Overview

    The provided text describes a 510(k) premarket notification for the NxStage System One, an hemodialysis system. The submission focuses on expanding the indications for use to include "solo home hemodialysis during waking hours." The study conducted is a Patient Preference Information (PPI) survey to support this indication expansion, not a typical performance study of an AI/ML device.

    Therefore, many of the requested elements for describing the acceptance criteria and the study that proves an AI/ML device meets those criteria are not applicable to this document. This document is about a medical device (hemodialysis system) and an expansion of its usage, supported by patient preference data, not an AI/ML algorithm.

    However, I will attempt to extract what is relevant and indicate where information is not present or not applicable based on this specific document.


    Analysis of the Provided Document for AI/ML Device-Specific Criteria:

    This document is a 510(k) summary for the NxStage System One, a hemodialysis device. The study described is a patient preference information (PPI) survey, not a study of an AI/ML device's performance. Therefore, many of the requests about AI/ML specific acceptance criteria, ground truth, expert adjudication, MRMC studies, standalone performance, and training sets are not applicable to the content of this document.

    The "acceptance criteria" here refer to the willingness of patients to accept certain risk profiles for solo home hemodialysis.

    Here's an attempt to answer the questions based on the provided text, highlighting what is (and isn't) present:


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

    The "acceptance criteria" in this context are thresholds of risk tolerance for solo home hemodialysis based on patient preferences. The 'performance' is indicated by the percentage of patients willing to choose Solo HHD under varying risk scenarios.

    Acceptance Criteria (Risk Threshold - for choice shift to In-Center HD)Reported "Performance" (% of patients choosing Solo HHD)
    Mortality Risk
    ≤16%135 (95%)
    >16% to 20%120 (85%)
    >20% to 25%97 (68%)
    >25% to 30%71 (50%)
    >30% to 35%56 (39%)
    Needle Dislodgement Risk Leading to Serious Injury
    ≤0.7%125 (88%)
    >0.7% to 2%107 (75%)
    >2% to 11%79 (56%)
    >11% to 33%51 (36%)
    >33% to 67%36 (25%)
    >67% to 100%27 (19%)

    Note: The "acceptance criteria" here are patient thresholds, not device performance metrics in a traditional sense. The 'performance' is how many patients still opt for Solo HHD at various risk levels.


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

    • Sample Size: 142 evaluable responses from patients.
    • Data Provenance: All dialysis centers and patients were located in the United States of America.
    • Study Design: This was a prospective survey conducted electronically with current HHD patients.

    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. This study is a patient preference survey, not a study evaluating a medical image or diagnostic output that would require expert ground truth. The "ground truth" here is the patient's stated preference regarding risk tolerance.


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

    Not applicable. There was no expert adjudication in this patient preference survey. Patient responses were the direct data.


    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

    Not applicable. This was not an MRMC study and did not involve human readers evaluating AI assistance.


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

    Not applicable. This study did not involve an algorithm with standalone performance.


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

    The "ground truth" for this study was patient preference information (PPI), specifically their stated willingness to choose solo home hemodialysis given varying hypothetical risk profiles (death, needle dislodgement).


    8. The sample size for the training set

    Not applicable. This study did not involve a machine learning model with a separate training set. It was a survey to gather patient preference data.


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

    Not applicable. As there was no training set for a machine learning model, this question is not relevant to the described study.

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