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The SCIMED guide catheters are designed to provide a pathway through which medical instruments, such as balloon dilatation catheters, guide wires or other therapeutic devices may be introduced. These devices are not intended for use in the cerebral vasculature.

The modified 6F-10F SCIMED guide catheter shafts consist of three layers: 1) the inner polytetrafluoroethylene (PTFE) layer that provides a low coefficient of friction and facilitates easy passage of medical devices such as balloon dilatation catheters, guide wires or other therapeutic devices, 2) the middle layer which is made of braided stainless steel wire that extends from the shaft to the tip to provide torque control and support and 3) the outer layer, manufactured from Pebax®, which provides stiffness, memory and radiopacity. The distal tip is made of Pebax and is radiopaque. The tip is heat fused to the distal end of the shaft. The catheters utilize a one piece Pebax hub/strain relief that is molded to the proximal end of the guide catheter shaft. The devices will be provided sterile and are intended for one procedure use only.

This is a 510(k) premarket notification for a medical device, specifically a coronary guide catheter. The document describes the device, its intended use, and a summary of non-clinical testing. However, it does not contain the kind of information typically found in a study proving an AI/ML device meets acceptance criteria.

Therefore, I cannot populate the requested table and answer the study-specific questions.

Here's why and what information is available:

Why the requested information is not present:

• Device Type: This submission is for a conventional medical device (a catheter), not an AI/ML powered device. The questions about AI/ML specific elements like sample sizes for test sets, data provenance, expert ground truth, adjudication methods, MRMC studies, or standalone algorithm performance are not relevant to this type of submission.
• Approval Type: A 510(k) submission generally relies on demonstrating substantial equivalence to a predicate device, as opposed to extensive clinical trials proving novel performance metrics, especially for physical devices.
• Time Period: The submission is from 1996, a time when AI/ML in medical devices was not prevalent or subject to the current regulatory scrutiny for such technologies.

Information that can be extracted or inferred from the provided text:

While I cannot provide a table of acceptance criteria for an AI/ML device or detailed study specifics you asked for, I can summarize the non-clinical testing mentioned for this specific catheter device.

Summary of Non-Clinical Testing for SCIMED® TRIGUIDE® Guide Catheters (K961280)

1. Table of Acceptance Criteria and Reported Device Performance:

Note: The document states "Test results verified that the modified catheter with the PTFE inner is adequate for its intended use." It does not provide specific numerical thresholds or detailed results for these tests, only that they passed.

2. Sample size used for the test set and the data provenance (e.g. country of origin of the data, retrospective or prospective):

• Sample Size: Not specified. The document only mentions "Functional testing consisted of..." without quantifying the number of devices or tests performed.
• Data Provenance: Not applicable. These were in-vitro (laboratory) tests performed on the device itself.
• Retrospective/Prospective: Not applicable. These were laboratory tests.

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. This was physical device testing, not expert-adjudicated data.

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

• Not applicable. This was physical device testing.

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/ML device.

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

• Not applicable. This is not an AI/ML device.

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

• Not applicable in the AI/ML sense. The "ground truth" here would be the physical properties and performance characteristics of the catheter as measured by standard engineering and mechanical tests.

8. The sample size for the training set:

• Not applicable. This is not an AI/ML device.

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

• Not applicable. This is not an AI/ML device.

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