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510(k) Data Aggregation

    K Number
    K102833

    Validate with FDA (Live)

    Date Cleared
    2011-11-18

    (415 days)

    Product Code
    Regulation Number
    876.5540
    Reference & Predicate Devices
    Predicate For
    N/A
    AI/MLSaMDIVD (In Vitro Diagnostic)TherapeuticDiagnosticis PCCP AuthorizedThirdpartyExpeditedreview
    Intended Use

    Disposable Hemodialysis Access Catheter Sets, including Single-lumen and Dual-lumen, are intended to attain long or short term (less than 30 days) vascular access for hemodialysis via the internal jugular, subclavian or femoral vein.

    Device Description

    Disposable Hemodialysis Access Catheter Sets, including Single-lumen and Dual-lumen, are intended to attain long or short term (less than 30 days) vascular access for hemodialysis via the internal jugular, subclavian or femoral vein. It consists of a catheter, a puncture needle, a guide wire and a dilator. The set is provided EO sterilized.

    AI/ML Overview

    The provided text describes a medical device, a "Disposable Hemodialysis Access Catheter Set," and its substantial equivalence to predicate devices, rather than a study proving the device meets specific acceptance criteria based on performance metrics such as accuracy, sensitivity, or specificity commonly associated with AI/ML devices or diagnostic tools.

    The "Test Conclusion" section outlines performance tests conducted, but these are primarily engineering, material, and sterilization validation tests, not clinical performance studies measuring effectiveness in a patient population or against specific clinical endpoints.

    Therefore, many of the requested elements for an AI/ML device or diagnostic tool study, such as sample size for test sets, data provenance, expert ground truth, adjudication methods, MRMC studies, standalone performance, and ground truth for training sets, are not applicable or cannot be extracted from this document.

    However, I can extract the acceptance criteria and the "reported device performance" in the context of the engineering and validation tests described.

    Here's the information based on the provided text, recognizing the limitations:

    1. Table of Acceptance Criteria and Reported Device Performance

    Acceptance Criteria CategorySpecific Criteria/TestReported Device Performance
    BiocompatibilityPer ISO 10993-1:2009"The test results were determined to be acceptable"
    Physical PerformancePer ISO 10555-1:1995/AMD.1:1999/AMD.2:2004(E) and ISO 10555-3:1996/AMD.1:1999, including: - Surfaces - Dimensions - Mechanical Strength - Leakage - Flow Rate - Fatigue"The test results demonstrated that the proposed devices comply with the performance standards"
    Recirculation & ClampingRecirculation and Repeated Clamp Tests(Implicitly acceptable as part of overall design specifications met)
    SterilizationPer ISO 11135-1:2006 (SAL of 10^-6, acceptable sterilant residual)"The results demonstrated that the sterilization method and cycle of the proposed device could reach SAL of 10^-6, and the sterilant residual was acceptable"
    Package IntegritySeal Strength, Internal Pressure, Dye Penetration"Performed to evaluate the package integrity of the proposed device to demonstrate that the immediate package could maintain the sterility during its shelf life." (Implicitly acceptable as meeting design specifications)

    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 for Test Set: Not specified. The document refers to "laboratory testing" and various ISO standards, which would involve a defined sample size for each test (e.g., number of catheters for mechanical strength, number of samples for biocompatibility), but these specific numbers are not disclosed in this summary.
    • Data Provenance: The tests were conducted by Foshan Nanhai Bai He Medical Technology Co., LTD, which is based in Foshan, Guangdong, China. These are laboratory data, not clinical patient data. The nature of these tests is prospective for the device under submission, meaning the tests were performed specifically for this 510(k) submission.

    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. These are engineering and material validation tests conducted in a laboratory setting against specified standards, not diagnostic or clinical performance studies requiring expert ground truth or assessment of patient data.

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

    • Not applicable. This concept pertains to resolving discrepancies in expert interpretations for clinical ground truth, which is not relevant to the described laboratory validation tests.

    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 is not an AI/ML device or a diagnostic imaging device subject to MRMC studies.

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

    • Not applicable. This is a physical medical device (catheter set), not an algorithm or AI solution.

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

    • For the described tests, the "ground truth" refers to the established specifications within the cited ISO standards (e.g., specific tensile strength values, defined biocompatibility parameters, required sterility assurance levels). These are objective, measurable parameters, not clinical ground truth derived from patient data.

    8. The sample size for the training set

    • Not applicable. This is not an AI/ML device that requires a "training set."

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

    • Not applicable. This is not an AI/ML device.
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    K Number
    K070451

    Validate with FDA (Live)

    Date Cleared
    2007-07-31

    (166 days)

    Product Code
    Regulation Number
    880.5200
    Reference & Predicate Devices
    Predicate For
    AI/MLSaMDIVD (In Vitro Diagnostic)TherapeuticDiagnosticis PCCP AuthorizedThirdpartyExpeditedreview
    Intended Use

    The Central Venous Catheters including:

    14 G, 16 G, 18 G, and 20 G in single-lumen catheters;

    4 F. 5 F, 7 F and 8 F in double-lumen catheter;

    5.5 F and 7 F in triple-lumen catheter;

    are intended for vascular access infusion and withdrawal of blood, blood products, and fluids, plasma pheresis, hyperalimentation, central venous blood sampling and continuous and intermittent drug infusion.

    Device Description

    Able® Central Venous Catheter is a polyurethane central venous catheter which is intended to insert into the patient's vascular system for short term use (less than 30 days) to sample blood, monitor blood pressure, or administer fluids intravenously.

    All the variants of applicant devices: single-lumen, and triple-lumen, and triple-lumen. There are outer diameter dimensions of 14 G, 16 G, 18 G, and 20 G in single-lumen catheters, 4 F, 5 F, 7 F and 8 F in double-lumen catheter, and 5.5 F and 7 F in triple-lumen catheter.

    The applicant device mainly consists of 5 parts: distal end, catheter body of effective length, catheter junction, extension cannula, and catheter hub. Distal end is soft and flexible, which is intended to be located within the patient's vena cava. Catheter body of effective length is tubular and with no-communication single or multiple lumens. Catheter junction attaches catheter body of effective length and extension cannula. At the end of the extension cannula, there is female catheter hub for the connection.

    AI/ML Overview

    The provided text is a 510(k) summary for a Central Venous Catheter, which is a medical device. The information requested in your prompt (Acceptance Criteria, Sample Sizes, Ground Truth, MRMC studies, etc.) is typically associated with AI/software-as-a-medical-device (SaMD) submissions, especially for diagnostic or predictive algorithms.

    The document you provided does not contain information related to AI/SaMD performance studies. It describes a physical medical device (catheter) and its testing against established physical and biological standards. Therefore, most of your specific questions cannot be answered from the given text.

    However, I can extract the relevant information regarding the device's testing and acceptance criteria as described:

    1. Table of Acceptance Criteria and Reported Device Performance

    The document states that the physical device testing was done in compliance with various ISO standards and internal tests. The acceptance criteria for these tests are generally that the device "conforms" or "is in compliance" with these standards, meaning it met the specifications outlined within them. The document does not provide specific numerical ranges for acceptance or detailed performance data for each test beyond stating compliance.

    Acceptance Criteria CategoryReported Device Performance
    Biological EvaluationIn compliance with ISO 10993
    Compatibility of Component MaterialProvided (implies satisfactory)
    Physical & Mechanical StandardsConforms to ISO 10555-1 and ISO 10555-3
    Specific Tests (e.g., Surface, Size, Flow Rate, Tensile Strength, Leakage, Radiodetectability etc.)Testing to Support Substantial Equivalence included; Assumed to have met acceptance criteria for substantial equivalence, though specific numerical results or criteria are not detailed.

    2. Sample Size used for the test set and the data provenance

    The document does not specify sample sizes used for each of the physical and biological tests conducted (e.g., how many catheters were tested for flow rate or tensile strength). The data provenance is implied to be from Foshan Nanhai Bai He Medical Technology Co., Ltd. in China, as they are the manufacturer and submitter. The tests described are "testing to support substantial equivalence," which suggests prospective testing performed on manufactured devices.

    3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts

    This question is not applicable. The device is a physical medical device (catheter), not an AI/SaMD that requires expert ground truth for diagnostic or predictive accuracy. The "ground truth" for this device is based on established engineering and materials science standards (e.g., ISO 10993, ISO 10555-1, ISO 10555-3).

    4. Adjudication method for the test set

    This question is not applicable. Adjudication methods like "2+1" or "3+1" are relevant for expert review of images or data in AI/SaMD studies. For a physical device, testing follows standardized methods, and results are typically objective measurements.

    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 question is not applicable. MRMC studies are used for evaluating the impact of AI on human reader performance, typically in diagnostic imaging. This document describes a physical medical device (catheter), not an AI application.

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

    This question is not applicable. This document describes a physical medical device, not an algorithm.

    7. The type of ground truth used

    The "ground truth" for this device's performance is based on predefined engineering specifications, material properties, and compliance with international standards (e.g., ISO 10993 for biocompatibility, ISO 10555-1 and ISO 10555-3 for intravascular catheters). These standards effectively serve as the "ground truth" against which the device's performance is measured.

    8. The sample size for the training set

    This question is not applicable. There is no AI algorithm described in this submission, so there is no "training set."

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

    This question is not applicable, as there is no AI algorithm or training set.

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