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The Flush Connector is indicated for providing hemostasis around catheters, guidewires and other devices during general intravascular procedures.

The Flush Connector consists of a main lumen body with a hemostasis valve at one end and a rotating male luer at the other end. In addition, the body has a side arm lumen with attached extension tube and female luer fitting. The haemostatic valve is designed to seal around a guide wire, stiffening wire, or other devices: and the side arm tubing is provided for fluid administration and flushing. The rotating male luer is designed to a female luer such as on a catheter. The proposed Flush Connector may be provided as a stand alone device or may be provided in a kit configuration with other legally marketed devices as a convenience to the user.

The provided text is a 510(k) summary for the Navilyst Medical Flush Connector. This document focuses on demonstrating substantial equivalence to a predicate device, rather than presenting a detailed study proving the device meets specific acceptance criteria with quantifiable performance metrics typically found in clinical trials or software validation studies.

Therefore, the information requested regarding acceptance criteria, device performance, sample sizes, expert involvement, adjudication, and ground truth establishment for a diagnostic AI/ML device is not directly available in this type of regulatory submission.

This document describes a physical medical device (Flush Connector) and its performance evaluation is done through a series of bench tests and biocompatibility assessments against established standards, not through clinical studies involving human readers or AI.

However, I can extract the relevant information from the document regarding the performance evaluation that was conducted:

1. Table of Acceptance Criteria and Reported Device Performance:

2. Sample size used for the test set and the data provenance:

• The document does not specify the exact sample sizes for each test mentioned (e.g., how many Flush Connectors were tested for leak, or how many iterations of a biocompatibility test were performed).
• The data provenance is not specified in terms of country of origin, but these are typically laboratory bench tests performed by the manufacturer or contracted labs. The tests are "retrospective" in the sense that they are performed on manufactured devices for regulatory submission, rather than prospective clinical data collection.

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

• This information is not applicable to the type of device and testing described. The "ground truth" for a physical device's performance is determined by adherence to established engineering and material science standards, not by expert consensus on interpretations.

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

• This concept is not applicable. Adjudication methods are relevant for subjective interpretations (e.g., image reading) where disagreement can occur. Bench tests provide objective pass/fail results or quantitative measurements that are typically not subject to such adjudication.

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 comparative effectiveness study was not done. This device is a physical medical component, not an AI/ML diagnostic tool or software.

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

• No, a standalone algorithm performance evaluation was not done. This device has no AI/ML component.

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

• The "ground truth" for this device's performance derives from established international and national standards (e.g., ISO, EN, ASTM, USP) for medical device functionality, materials, sterilization, and biocompatibility. Compliance with these standards serves as the "ground truth" that the device is safe and effective for its intended use as a physical connector.

8. The sample size for the training set:

• This is not applicable. The device is not an AI/ML model and therefore does not have a "training set."

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

• This is not applicable. The device is not an AI/ML model and therefore does not have a "training set" or a ground truth established for it in that context.

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