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Distal Access torque devices are used to maneuver quide wires in the coronary and peripheral vasculature during interventional or diagnostic procedures. Distal Access torque devices are not intended for use in the neurovasculature.

The Distal Access Torque Device (Predict / Spinr Controller) is a single-use hand-held manually operated high-performance torque device / controller used to maneuver difficult-to-grasp devices including quidewires during interventional or diagnostic procedures. The Predict's design allows for predictable and controllable rotation of a device clockwise with counterclockwise return to its original orientation. Clockwise and counterclockwise rotations are manually controlled so the Predict rotates the same number of rotations in one direction as the other. Similar to the predicates, the user manually advances and retracts the Predict torque device forward and backward to introduce or remove the connected device from the body. Also, identical to the predicates, the Predict may be connected to a device already in the body. Same as the predicates, a device, including a guidewire, is loaded into the Predict 0.014 - 0.039" by inserting the proximal end of the device into the distal end of the Predict's cap. The Predict locks down on the device when the user rotates the collet cap clockwise, forcing the industry standard designed collet to grip onto the device is released when the user rotates the cap counterclockwise to loosen the collet's grip on the device. Once a device is connected, the Predictably rotates devices between 3 and 5 times clockwise and counterclockwise as per the labeled number of rotation is manually controlled by the user's finger, thumb and hand. Also, identical to predicates, the Predict does not use electrical power or software.

This document is primarily a 510(k) summary for the Distal Access Torque Device (Predict or Spinr). It details the device's description, indications for use, and a comparison to predicate devices, focusing on demonstrating substantial equivalence. The document does not contain an acceptance criteria table or information typically found in an independent study report, such as specific performance metrics and their acceptance limits.

However, based on the provided text, I can infer some criteria and the general nature of the "study" (non-clinical testing) conducted.

Here's an attempt to answer your request based on the available information:

1. Table of Acceptance Criteria and Reported Device Performance

The document does not provide a formal table of acceptance criteria with specific numerical limits and corresponding performance results. Instead, it lists attributes evaluated and states: "The Predict subject device met all predetermined acceptance criteria identified in test protocols created to evaluate conformance with the relevant requirements of the above listed standards, guidance documents, and in-house protocols demonstrating that identified potential risks and hazards have been acceptably controlled and that the safety and/ or performance of the new device are equivalent to those of the cited predicate device(s)."

Here's a table based on the evaluated attributes and the general statement about meeting acceptance criteria:

2. Sample Size Used for the Test Set and Data Provenance

The document mentions "Verification and validation tests" and "in-house protocols" for testing of the Predict device. However, it does not specify sample sizes for any of the tests conducted.

• Data Provenance: The data is from "in-house protocols" and "nonclinical tests" conducted by Distal Access, LLC. The country of origin is not explicitly stated, but the company address is in Park City, UT, USA. The data is retrospective in the sense that the tests were performed on finished devices to support the 510(k) submission, not as part of a prospective clinical trial.

3. Number of Experts Used to Establish the Ground Truth for the Test Set and Qualifications of Those Experts

This information is not provided in the document. The tests appear to be engineering and laboratory-based performance tests, not human-reader-based assessments where "ground truth" established by experts would typically be relevant.

4. Adjudication Method for the Test Set

This information is not applicable as the tests are non-clinical engineering and performance evaluations, not diagnostic assessments requiring adjudication of human interpretations.

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, an MRMC comparative effectiveness study was not done. This device is a manual torque device, not an AI-assisted diagnostic tool.
• The concept of human readers improving with AI vs without AI assistance is not applicable to this type of medical device.

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

• No, a standalone algorithm performance study was not done. This device is a mechanical tool operated by a human, not a software algorithm.

7. The Type of Ground Truth Used

The "ground truth" for the non-clinical performance and safety tests were established by engineering specifications, regulatory standards (e.g., ISO 10993, ANSI/AAMI/ISO 11135-1, ASTM F88, ASTM F1980-07), and internal design protocols. For instance, a test for "axial wire retention force" would have a defined minimum force that the device must withstand before the wire slips, and successfully meeting this force would be the "ground truth" for that attribute.

8. The Sample Size for the Training Set

This information is not provided and is not applicable. The device is a mechanical tool, not an AI system that requires a "training set" of data.

9. How the Ground Truth for the Training Set Was Established

This information is not applicable as there is no "training set" for this type of device.

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