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510(k) Data Aggregation

    K Number
    K183036
    Device Name
    Dilator Sets
    Manufacturer
    Date Cleared
    2018-12-20

    (49 days)

    Product Code
    Regulation Number
    870.1310
    Reference & Predicate Devices
    Why did this record match?
    Reference Devices :

    K170020, K171264, K161801

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

    Intended to be used for dilating puncture sites or catheter tracts for percutaneous placement of devices for vascular and non-vascular applications such as in the venous, arterial, biliary and renal systems.

    Device Description

    Cook Dilator Sets may consist of either a single dilator or a group of components that are used percutaneously to dilate puncture sites or catheter tracts, thereby facilitating the placement of other therapeutic or diagnostic devices into a natural body space (e.g., the peritoneal cavity, an artery or vein) for various vascular or non-vascular clinical applications. Some Dilator Set configurations may also include an entry needle and wire guide. The dilator component of the Dilator Sets is available in diameters ranging from 3.0 to 26.0 French and in lengths ranging from 6 to 65 cm. The broad range of dilator sizes accommodates the variation in the size of the devices that could be inserted through the initial access site. All configurations of the Dilator Sets are supplied as packaged, sterile devices, intended for single-patient use.

    AI/ML Overview

    This document describes the premarket notification for Dilator Sets manufactured by Cook Incorporated. It's a 510(k) submission, meaning the company is demonstrating that their device is "substantially equivalent" to legally marketed predicate devices, rather than proving its safety and effectiveness from scratch like a PMA would entail.

    Therefore, the information provided focuses on comparative performance and compliance with relevant standards, not on a full-scale clinical study with human-in-the-loop performance or detailed AI model training/testing.

    Here's an analysis of the provided text in response to your request:

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

    The document states that the device was subjected to various tests and "The pre-determined acceptance criteria were met" for all of them. However, it does not explicitly list the quantitative acceptance criteria for each test, nor does it provide the specific numerical performance results. It only confirms compliance.

    Test NameAcceptance Criteria (Stated in Document)Reported Device Performance (Stated in Document)
    BiocompatibilityPre-determined acceptance criteria metMet the pre-determined acceptance criteria
    Dilator Hub to Shaft TensilePre-determined acceptance criteria metMet the pre-determined acceptance criteria
    Compatibility TestingPre-determined acceptance criteria metMet the pre-determined acceptance criteria
    Dimensional VerificationPre-determined acceptance criteria metMet the pre-determined acceptance criteria
    Radiopacity EvaluationPre-determined acceptance criteria metMet the pre-determined acceptance criteria
    Dilator Tip RollbackPre-determined acceptance criteria metMet the pre-determined acceptance criteria
    Kink RadiusPre-determined acceptance criteria metMet the pre-determined acceptance criteria
    Lubricity TestingPre-determined acceptance criteria metMet the pre-determined acceptance criteria

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

    The document does not specify the sample sizes used for any of the tests. Given this is a 510(k) submission for a physical medical device, the "data provenance" would refer to the location and conditions of the lab testing, which are not detailed here. There's no mention of specific patient data, as this is not an AI/software device or a clinical trial report.

    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)

    This question is not applicable to the provided document. The "ground truth" in this context is established by engineering standards and validated test methods (e.g., ISO 10993-1, ISO 11070, ASTM F640-12), not by expert consensus on clinical data interpretation. Therefore, there's no mention of experts establishing a "ground truth" for a test set in the way one would for an AI diagnostic device.

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

    Not applicable. Adjudication methods like 2+1 or 3+1 are typically used in clinical studies where multiple readers assess and come to a consensus on image interpretation or diagnosis. The tests performed here are engineering and material property tests conducted under specific protocols, not expert clinical reviews.

    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 a physical medical device (dilator sets), not an AI-assisted diagnostic tool. Therefore, no MRMC studies or human reader improvement analysis were conducted or are relevant to this submission.

    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 or software. Its performance is evaluated through physical and material property tests, not through standalone algorithm performance.

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

    The "ground truth" for the device's performance is based on established international and industry standards and approved study protocols for medical device testing. For example:

    • Biocompatibility: ISO 10993-1:2009
    • Dilator Hub to Shaft Tensile: ISO 11070:2014
    • Radiopacity: ASTM F640-12
    • Dilator Tip Rollback: ISO 11070:2014, Annex A.3
    • Kink Radius: ISO 11070:2014, Annex A

    These standards define methods and typically acceptable performance ranges or pass/fail criteria, which serve as the "ground truth" for these engineering tests.

    8. The sample size for the training set

    Not applicable. This device does not involve machine learning or AI, so there is no concept of a "training set."

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

    Not applicable, as there is no training set.

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