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The Rüsch Brillant Silicone Foley is used to drain fluids to and from the urinary tract.

The Rusch Brillant Silicone catheter is of the retention type, commonly called a Foley catheter. The device is a single use, disposable, sterile with retention balloon, which is attached to the silicone shaft. One lumen is for draining fluids to and from the urinary tract. The second lumen is to inflate and deflate the balloon with sterile water. On models with a third lumen, it is used in conjunction with the first lumen for flushing the urinary tract. Sterile water is used for inflation and deflation of the balloon. The distal end has two opposite eye holes, which are used for drainage. On the opposing end of the shaft, are a connecting funnel and a Luer activated valve. Pediatric sizes of this product are used with a stylet that is inserted prior to the catheter placement. This product is available in sizes 8 Fr to 26 Fr.

Here's an analysis of the provided text regarding acceptance criteria and supporting studies, formatted as requested.

Based on the provided 510(k) summary for the Rüsch Brillant Silicone Foley catheter, there is no information about a study proving the device meets specific performance-based acceptance criteria in the context of AI/software device evaluation.

The document is a traditional 510(k) for a physical medical device (a catheter), which focuses on substantial equivalence to a predicate device rather than performance metrics of an AI algorithm. Therefore, many of the requested fields are not applicable in this context.

Here's an attempt to answer the questions based on the available information, noting where information is absent or irrelevant to AI/software performance studies:

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

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. This submission is for a physical medical device (catheter) and does not involve a "test set" of data for evaluating an AI or software algorithm. The evaluation is based on substantial equivalence to a predicate device, material properties, and manufacturing controls.

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. As above, there is no "test set" or "ground truth" establishment in the context of an AI/software performance study for this device. The regulatory review focuses on engineering, materials, and clinical equivalence rather than expert interpretation of data.

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

• Not Applicable. No test set requiring expert 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

• Not Applicable. This is not an AI-assisted device.

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

• Not Applicable. This is not an AI algorithm.

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

• Not Applicable. Any "ground truth" related to this physical device would refer to established engineering standards, material specifications, and clinical performance of the predicate device, not ground truth for an AI assessment.

8. The sample size for the training set

• Not Applicable. This is not an AI/machine learning device.

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

• Not Applicable. This is not an AI/machine learning device.

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