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The Hemostasis Valve is intended to maintain a fluid-tight seal around interventional and diagnostic devices during use.

The Hemostasis Valve is a valve consisting of a clear polycarbonate body, silicone valve, polyacetal actuation lever, and polycarbonate and EPDM o-ring rotating male Luer lock connector and female Luer lock.

This document, a 510(k) Premarket Notification for a Hemostasis Valve, does not contain the level of detail regarding acceptance criteria and study design that would be found in a clinical trial report or a more extensive study. The information provided focuses on demonstrating substantial equivalence to a predicate device rather than a comprehensive evaluation against specific performance metrics for a novel technology like an AI-powered device.

Therefore, many of the requested categories cannot be populated from the provided text.

Here's a breakdown of what can be extracted and what cannot:

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

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

• Not explicitly stated. The document refers to "performance data provided" but does not detail the sample size or the nature of the tests conducted (e.g., in-vitro, ex-vivo, in-vivo studies). Data provenance is also not mentioned.

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/Not stated. This type of information is relevant for studies involving qualitative assessments, such as image interpretation by medical professionals, which is not the case for this mechanical device.

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

• Not applicable/Not stated. Adjudication methods are typically used when there's subjective interpretation or disagreement among experts, which doesn't seem to be relevant for the mechanical performance testing of a valve.

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 device is a mechanical hemostasis valve, not an AI-powered diagnostic or assistive tool for human readers. Therefore, an MRMC study is irrelevant.

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

• Not applicable. This device is a mechanical hemostasis valve, not an algorithm or AI system.

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

• Implied engineering and performance standards. For a mechanical device like a hemostasis valve, the "ground truth" would likely be established through engineering specifications, validated test methods (e.g., leakage tests, pressure tests, material compatibility tests), and comparison to the predicate device's established performance. The document states that the technological characteristics are "similar in design and technology" to the predicate.

8. The sample size for the training set

• Not applicable. This information pertains to machine learning models, not the development of a mechanical device.

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

• Not applicable. This information pertains to machine learning models, not the development of a mechanical device.

Summary based on the provided text:

The provided document describes a 510(k) premarket notification for a Hemostasis Valve. The acceptance criteria are implicitly that the device is safe and effective for its intended use, specifically to "maintain a fluid-tight seal around interventional and diagnostic devices during use," and that its component materials are biocompatible. The study proving this involves "performance data provided" and biocompatibility statements, along with a comparison of its design and technology to a legally marketed predicate device (Merit Passage® Hemostasis Valve, K925419).

The document is a regulatory submission for a traditional medical device, not an AI/ML-powered device. Therefore, many of the questions related to AI-specific study design (e.g., training sets, expert ground truth, MRMC studies) are not applicable to this context and are not addressed in the provided text. The "study" here refers to the testing and comparison performed by the manufacturer to demonstrate substantial equivalence, rather than a clinical trial with human subjects or a formal AI performance evaluation.

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