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The Route 92 Medical Sheath System is indicated for the introduction of interventional devices into the peripheral and neuro vasculature.

The Route 92 Medical Sheath System is comprised of a Sheath, a Dilator, a Navigating Catheter, and an RHV (rotating hemostasis valve). The Sheath is a single-lumen, variable stiffness catheter with a radiopaque marker on the distal end. The inner lumen of the catheter is compatible with 8F or smaller catheters. The Dilator may be placed within the Sheath to facilitate percutaneous introduction of the Sheath into a femoral artery. The Dilator has a radiopaque marker at the distal tip. The Navigating Catheter is a single-lumen, variable stiffness catheter with a radiopaque marker at the distal tip. The Navigating Catheter is compatible with the Sheath and has a shaped distal end to facilitate placement. All of the catheters are coated with hydrophilic coating.

The provided text describes the 510(k) summary for the Route 92 Medical Sheath System, which is a medical device. This type of submission focuses on demonstrating substantial equivalence to a predicate device rather than conducting a de novo study to establish new acceptance criteria and prove its performance. Therefore, the information requested about acceptance criteria and a study proving the device meets those specific acceptance criteria (as would be applied to a novel device or AI software) is not directly present in the provided document.

Instead, the document details non-clinical testing to demonstrate the device's safety and performance against established standards and equivalence to a predicate device. The "acceptance criteria" here are implicitly the "PASS" results for each test, indicating conformity to pre-determined specifications or regulatory requirements.

Here's an attempt to answer your questions based on the provided text, while acknowledging the focus on substantial equivalence:

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

Since this is a 510(k) submission, the acceptance criteria are not explicitly defined numerical targets specific to a new AI model's performance but rather general standards and successful completion of tests demonstrating safety and equivalence.

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 generally states "All samples met the pre-determined acceptance criteria" for performance tests and provides results for biocompatibility tests (e.g., "All animals treated had were clinically normal" for acute systemic toxicity). It does not specify precise sample sizes for each non-clinical test.

• Sample Size: Not explicitly stated for most tests, often referred to as "all samples" or "animals" depending on the test type.
• Data Provenance: Not applicable in the context of these non-clinical, lab-based tests on device components/products. The tests are designed to evaluate the physical and biological characteristics of the device itself, not data from human subjects or retrospective/prospective studies in the clinical sense.

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 is not applicable. The tests conducted are non-clinical, laboratory-based evaluations of device properties (e.g., tensile strength, biocompatibility, dimensions). They do not involve expert interpretation of data or images to establish a "ground truth" as would be required for an AI-powered diagnostic device.

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

This is not applicable for non-clinical, laboratory-based testing of device characteristics. Adjudication methods are typically used in clinical studies or for establishing ground truth in diagnostic accuracy studies involving human interpretation.

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

No. The provided document is for a "Percutaneous Catheter" device, which is a physical medical instrument, not an AI software. Therefore, an MRMC comparative effectiveness study involving human readers and AI assistance is not relevant and was not conducted.

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

No. This is a physical medical device, not an algorithm or AI.

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

This is not applicable as the tests are non-clinical hardware evaluations. The "ground truth" broadly refers to the established scientific and engineering principles, international standards (e.g., ISO), and pre-determined specifications against which the device's performance is measured.

8. The sample size for the training set

This is not applicable as the device is a physical medical instrument and no AI/machine learning model was trained.

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

This is not applicable as there is no training set for an AI/machine learning model.

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