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The IYUNNI™ 3ID Tri-Funnel Gastrostomy Tube Kit is indicated for use in percutaneous placement of a gastrostomy tube for feeding and/or medication in conjunction with an established gastrostomy tract, or using a Stamm Procedure. The gastrostomy tube may also be used for gastric decompression.

The IYUNNI™ 3ID Tri-Funnel Gastrostomy Tube Kit is a gastrostomy tube kit. The kit components include the IYUNNI™ Soft Tip Introducer Dilator.

The provided text describes a 510(k) premarket notification for a medical device and, as such, does not contain information about a study based on the criteria you've outlined for evaluating the performance of AI/ML-driven devices.

The document is for the IYUNNI™ 3ID Tri-Funnel Gastrostomy Tube Kit, which is a physical medical device (a gastrostomy tube), not a software or AI/ML diagnostic tool. Therefore, the concepts of "acceptance criteria," "reported device performance," "sample size for test set," "data provenance," "experts to establish ground truth," "adjudication method," "MRMC comparative effectiveness study," "standalone performance," "type of ground truth," "training set sample size," or "how ground truth for training set was established" are not applicable in the context of this submission.

Instead, the submission focuses on demonstrating substantial equivalence to existing, legally marketed predicate devices. This is a regulatory pathway for lower-risk devices where the primary evidence of safety and effectiveness comes from showing that the new device has similar technological characteristics and performs comparably to a device already cleared by the FDA.

Here's how the provided information relates to the acceptance criteria for a physical medical device's 510(k) submission:

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

• Acceptance Criteria: For this type of device, "acceptance criteria" are not reported as specific performance metrics like sensitivity/specificity. Instead, acceptance is based on demonstrating substantial equivalence to predicate devices, meaning the new device is as safe and effective as the predicate. This is typically shown by comparing design, materials, indications for use, and performance characteristics (e.g., sterilization methods, packaging) to the predicate devices.
• Reported Device Performance: The document explicitly states: "The components of the IYUNNI™ 3ID Tri-Funnel Gastrostomy Tube Kit has the same characteristics as those devices that are currently marketed. There is no change in the performance characteristics or intended use." The performance is implicitly "equivalent to the predicate devices."

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

• Not applicable. There is no "test set" in the sense of a dataset for algorithm evaluation. The evaluation is based on a comparison of device characteristics and intended use.

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

• Not applicable. There is no ground truth establishment for a diagnostic algorithm.

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

• Not applicable.

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-assisted diagnostic device.

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

• Not applicable.

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

• Not applicable.

8. The sample size for the training set:

• Not applicable.

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

• Not applicable.

In summary: The provided document is a 510(k) summary for a physical medical device (a gastrostomy tube kit) and relies on demonstrating substantial equivalence to predicate devices rather than the types of performance studies and metrics that would be applicable to an AI/ML diagnostic or assistive device. The "acceptance criteria" are met by matching the safety and effectiveness profile of already cleared devices through design, material, and functional comparisons.

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