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Used to establish a conduit during endoscopic urological procedures facilitating the passage of endoscopes and other instruments into the urinary tract. The Cook® Pediatric Flexor Ureteral Access Sheath is intended for Pediatric Use in patients two years of age and older.

The Cook® Pediatric Flexor Ureteral Access Sheath is used to establish a conduit during endoscopic urological procedures facilitating the passage of endoscopes and other instruments into the urinary tract. The Cook® Pediatric Flexor Ureteral Access Sheath is intended for Pediatric Use in patients two years of age and older.

The Cook® Pediatric Flexor Ureteral Access Sheath is a single use sterile device that is offered as a single or dual lumen device. The Cook® Pediatric Flexor Ureteral Access Sheath will be offered in a 9.5 French inside diameter length or 12 French inside diameter 13 centimeter length single lumen version. The Cook® Pediatric Flexor Ureteral Access Sheath will also be offered in a 9.5 French inside diameter 13 centimeter length or 12 French inside diameter 13 centimeter length dual lumen version. The main lumen of the 9.5 French dual lumen version is 9.5 French inside diameter and the main lumen of the 12 French dual lumen version is 12 French inside diameter. The secondary lumen on both sizes is 3 French inside diameter. Both versions inside diamster. The occurrently a Hydrophilically coated which, when activated, allows easier insertion and removal of the sheath.

The construction materials of the Cook® Pediatric Flexor Ureteral Access Sheath are all well known in the medical field. Biocompatibility testing has shown the materials to meet the test requirements. Bench top testing, coefficient of friction testing, irrigation flow study, buckling require test, kink resistance testing, risk analysis, complaints verses sales data, clinical feedback, and published articles support our claim that the device is as safe and effective in the pediatric population as in adult use.

The provided text is a 510(k) summary for the Cook® Pediatric Flexor Ureteral Access Sheath. It describes the device, its intended use, and claims substantial equivalence to predicate devices. However, this document does not contain acceptance criteria or a study proving the device meets specific acceptance criteria in the manner typically expected for AI/ML-based medical devices.

Instead, the submission relies on demonstrating substantial equivalence to already marketed predicate devices by showing similarities in:

• Indications for use
• Materials
• Physical construction
• Manufacturing process controls
• Quality Assurance Program
• Packaging and sterilization procedures

The document mentions various testing performed, but these are general engineering tests (e.g., biocompatibility, coefficient of friction, irrigation flow, buckling, kink resistance) to ensure the device's basic functionality and safety, rather than performance metrics against specific clinical acceptance criteria for an AI algorithm.

Therefore, for most of the requested information, the answer will be "Not Applicable" or "Not Provided" because the document does not describe an AI/ML-based device being validated against clinical performance criteria.

Here's a breakdown of the requested information based on the provided text:

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 document describes a physical medical device, not an AI/ML algorithm that would have a test set of data. The "testing" mentioned refers to engineering and biocompatibility tests of the device itself.

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. There is no mention of "ground truth" establishment by experts in the context of validating an AI/ML algorithm's output. The "clinical feedback" likely refers to general medical professional input regarding the device's design and use, not a formal ground truth process for a test set.

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

Not Applicable. There is no test set or adjudication method described for establishing ground truth for AI/ML performance.

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 submission does not describe an AI/ML device or a MRMC study.

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

Not Applicable. This submission does not describe an AI/ML device.

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

Not Applicable. There is no mention of ground truth in the context of an AI/ML algorithm.

8. The sample size for the training set

Not Applicable. This submission does not describe an AI/ML algorithm that would have a training set.

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

Not Applicable. This submission does not describe an AI/ML algorithm that would have a training set or associated ground truth.

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