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Self-Cath and Self-Cath Plus are intended for use in male, female and pediatric patients (neonates, infants, children, adolescents, and transitional adolescents) requiring bladder drainage as determined by their physician. The devices are indicated for those individuals unable to promote a natural urine flow or for those individuals who have a significant volume of residual urine following a natural bladder-voiding episode.

Self-Cath and Self-Cath Plus devices are single-use, sterile catheters for intermittent urinary catheterization. Self-Cath is an uncoated catheter and Self-Cath Plus has a hydrophilic-coating. The catheters are sterilized by ethylene oxide (EO).

The provided text describes the submission for FDA clearance of the "Self-Cath and Self-Cath Plus" devices (K221401).

Since this document is a 510(k) summary for a medical device and not for an AI/ML algorithm, the requested information pertaining to AI/ML specific criteria (such as number of experts for ground truth, adjudication methods, MRMC studies, standalone performance of an algorithm, training set sample size, etc.) is not applicable and therefore not present in the text.

However, I can extract the acceptance criteria and performance data for the device based on the information provided.

1. Table of Acceptance Criteria and Reported Device Performance

This pertains to the physical and chemical properties of the catheters, not an AI/ML algorithm.

Study Information (Based on device testing, not AI/ML algorithm)

2. Sample size used for the test set and the data provenance (e.g., country of origin of the data, retrospective or prospective)
The document does not specify the sample size used for performance testing (e.g., number of catheters tested for each criterion) or the data provenance. It states that "Performance testing for Self-Cath and Self-Cath Plus was conducted per applicable sections of non-recognized and recognized voluntary consensus standards, as well as established internal methods."

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)
This question is not applicable as this is a physical medical device clearance, not an AI/ML diagnostic or prognostic tool requiring expert ground truth for image/data interpretation.

4. Adjudication method (e.g., 2+1, 3+1, none) for the test set
This question is not applicable for a physical medical device. Performance testing relies on objective measurements against established standards, not subjective 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
This question is not applicable as this is a physical medical device, not an AI-assisted diagnostic tool.

6. If a standalone (i.e., algorithm only without human-in-the loop performance) was done
This question is not applicable as this is a physical medical device, not an AI algorithm.

7. The type of ground truth used (expert consensus, pathology, outcomes data, etc.)
For a physical medical device like a catheter, the "ground truth" for performance testing is defined by compliance with established international and ASTM standards (e.g., specific tensile strength, elongation, biocompatibility limits, flow rates, etc.) and internal methods, verifiable through objective experimental measurements.

8. The sample size for the training set
This question is not applicable as this is a physical medical device, not an AI/ML algorithm that requires a "training set."

9. How the ground truth for the training set was established
This question is not applicable as this is a physical medical device, not an AI/ML algorithm.

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