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The Artimes pro Balloon Dilatation Catheter is indicated for initial balloon dilatation of the stenotic portion of a coronary artery in patients with myocardial ischemia.

The Artimes pro (Rx type) device is a coronary dilatation catheter designed for easy guidewire exchange. The catheter working length is 140cm. Lubricious coatings are applied to the distal section. Balloon diameters range from 1.0mm to 1.25mm. The balloon material is made of a semi-compliant material for diameter 1.0mm to 1.25mm with a rated burst pressure of 14 atmospheres. The proximal shaft of the catheter is composed of a female luer connector bonded to a PTFE coated stainless steel tube with a wire. The proximal shaft joins with a smooth transition to a distal shaft composed of an outer tube and a tri-extrusion inner tube with a balloon laser welded to both tubes at the distal tip. The catheter has one radiopaque platinum/iridium marker band. The inner tube accepts a standard 0.014 inch PTCA guidewire. The guide wire enters the catheter tip and advances coaxially out the distal Rx port, thereby allowing both coaxial guidance and rapid exchange of catheter with a single standard length guide wire. Two marked sections of 5mm length each located on the proximal shaft indicate catheter position relative to the tip of either a brachial or femoral guiding catheter. The design of this dilatation catheter does not incorporate a lumen for distal dye injections or distal pressure measurements.

The provided text is a 510(k) clearance letter for a medical device, specifically the Artimes pro Balloon Dilatation Catheter. It outlines the regulatory approval process and states that the device has been found substantially equivalent to predicate devices. However, this document does not contain the specific details about the acceptance criteria and the comprehensive study results as typically required for an AI/ML-based device.

The "study" mentioned in the document is a Good Clinical Practice (GCP) clinical study for the physical medical device (catheter), not a study assessing the performance of an AI/ML algorithm. Therefore, many of the requested points related to AI/ML device evaluation (like ground truth establishment, expert adjudication, MRMC studies, etc.) are not applicable to the information contained within this document.

Here's a breakdown of the information that can be extracted, and where the requested information is not present in this document:

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)

• Sample Size (Clinical Study): Sixty (60) study subjects and sixty-one (61) target lesions.
• Data Provenance: Not specified in this document (e.g., country of origin, retrospective/prospective). However, the mention of "GCP clinical study" implies it was prospective data collected under Good Clinical Practice guidelines.

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 / Not present in the document. This document describes a physical medical device, not an AI/ML system requiring expert-established ground truth for a test set. This type of information would be relevant for devices that use AI to interpret medical images or data.

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

• Not applicable / Not present in the document. Adjudication methods are typically used when multiple experts review data for the purpose of establishing ground truth for AI algorithms. This document doesn't pertain to an AI algorithm.

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 / Not present in the document. MRMC studies are specific to evaluating AI/ML systems that assist human readers in tasks like image interpretation. This document is about a physical catheter.

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

• Not applicable / Not present in the document. This document is for a physical medical device, not an AI algorithm.

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

• For the clinical study: The "effectiveness" of the catheter would likely be assessed based on clinical outcomes relevant to balloon dilatation, such as successful dilatation of the stenotic portion of a coronary artery and improved myocardial perfusion, which would be observed during the procedure and in follow-up. This is a form of outcomes data or clinical assessment rather than expert consensus on images.

8. The sample size for the training set

• Not applicable / Not present in the document. There is no mention of a "training set" as this is not an AI/ML device. The "training set" concept is relevant for machine learning model development.

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

• Not applicable / Not present in the document. As above, no AI/ML training set is mentioned or implied.

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