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Two-way Disposable Silicone Foley Catheterization for bladder drainage and urological use only; the indwelling time is no more than 30 days.

Three-way Disposable Silicone Foley Catheterization for bladder drainage and bladder irrigation for urological use only; the indwelling time is no more than 30 days.

The Silicone Foley Catheter for single use is designed as an intermittent pathway for drainage and irrigation of the bladder. The device is made of silicone. The catheter is provided sterile in a variety of lengths and sizes.

The provided document is a 510(k) premarket notification for a medical device (Silicone Foley Catheter for single use). Such submissions are designed to demonstrate substantial equivalence to a legally marketed predicate device, not necessarily to prove specific performance against a detailed set of acceptance criteria in the manner requested for an AI/ML powered device.

Therefore, much of the requested information regarding acceptance criteria, specific study design for proving performance, and expert ground truth establishment for AI/ML devices is not applicable to this traditional medical device submission.

Here's an analysis based on the information provided in the document:

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

For a traditional medical device like a Foley catheter, "acceptance criteria" are typically defined by recognized standards and benchmarks set by the predicate device, rather than a quantifiable performance metric for an AI system. The document focuses on demonstrating substantial equivalence to a predicate device.

The "performance" is implicitly demonstrated through adherence to relevant standards and direct comparison of specifications with the predicate.

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

• Test Set Sample Size: The document does not specify exact sample sizes for each non-clinical test (e.g., how many catheters were tested for biocompatibility or physical performance). It only states that the tests were "conducted" and "evaluated." For a traditional device, testing is typically done on a representative sample to ensure consistency and compliance with standards.
• Data Provenance: The tests are non-clinical (laboratory-based performance and biocompatibility). The manufacturer is CHANGZHOU RONGXIN MEDICINE MINIMAL INVASION TECHNOLOGY CO., LTD., located in China. The data would originate from their internal testing or third-party labs they commissioned. The studies are by nature prospective as they are specifically conducted to support market clearance.

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

This question is not applicable. For a traditional catheter, "ground truth" is established by adherence to engineering specifications, material science, and performance standards, not by expert human interpretation of medical images or data (as would be the case for an AI/ML device). The "experts" involved would be engineers, material scientists, and quality assurance personnel performing the tests according to established protocols.

4. Adjudication method for the test set

Not applicable in the context of a traditional device. Adjudication methods (like 2+1, 3+1 for consensus readings) are relevant for subjective human interpretations, particularly in medical image analysis for AI. For device testing, results are typically objective measurements or pass/fail criteria according to a standard.

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 physical medical device, not an AI/ML software. Therefore, no MRMC study or AI assistance evaluation was performed.

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

Not applicable. This query refers to AI/ML algorithm performance. The device is a physical catheter.

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

As mentioned in point 3, the concept of "ground truth" as applied to AI/ML or diagnostic studies is not directly transferable here. Instead, compliance with recognized industry standards (e.g., ASTM, EN, ISO for biocompatibility) and direct comparison to the predicate device's established specifications serve as the "ground truth" for substantial equivalence.

8. The sample size for the training set

Not applicable. This device is not an AI/ML algorithm. There is no "training set."

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

Not applicable. There is no training set as this is not an AI/ML device.

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