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The Agilis™ PF Introducer System is intended to access the epicardial surface of the heart via a subxiphoid approach to facilitate electrophysiology studies.

The St. Jude Medical Agilis™ PF Introducer System consisting of an introducer, guidewire, 17Ga Tuohy needle, dilator and obturator is intended to be used to facilitate delivery of SJM devices into the pericardial space for diagnostic and therapeutic purposes.

The Agilis™ PF Introducer System consists of the following components: Deflectable introducer, 13 French, Dilator, Guidewire, Obturator, 17Ga Tuohy Needle.

The deflectable introducer is fitted with a hemostasis valve to minimize air introduction during introducer insertion and/or exchange. A sideport with a three-way stopcock is provided for air or blood aspiration and fluid infusion. A handle equipped with a deflection control mechanism deflects the tip up to 90° both clockwise and counterclockwise. The introducer features a radiopaque tip marker to improve fluoroscopic visualization.

This is a 510(k) summary for the St. Jude Medical Agilis™ PF Introducer System. This document focuses on demonstrating substantial equivalence to a predicate device and does not contain detailed acceptance criteria and a study proving those criteria are met in the same way one might find in a clinical trial report or a performance study for an AI/ML device.

However, based on the provided text, we can infer some "acceptance criteria" through the comparison to the predicate device and the general safety and effectiveness considerations for a medical device of this type. The "study" proving these criteria are met is the "performance testing" referenced implicitly in the comparison.

Here's a breakdown of the requested information, acknowledging the limitations of this type of regulatory submission:

1. Table of Acceptance Criteria and Reported Device Performance

Given that this is a 510(k) summary, explicit, quantifiable acceptance criteria with corresponding performance metrics (like sensitivity, specificity, accuracy for AI/ML) are not provided. Instead, the "acceptance criteria" are generally implied to be "substantially equivalent performance" to the predicate device, across various aspects.

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

This document is a 510(k) premarket notification for a medical device (an introducer system), not a data-driven AI/ML study. Therefore, there is no mention of a "test set" sample size or data provenance in the context of an algorithmic performance evaluation. The "performance testing" mentioned likely refers to bench testing, mechanical testing, and potentially animal studies to demonstrate physical equivalence and safety, but details are not provided in this summary.

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

As this is not an AI/ML study, there is no mention of experts establishing a ground truth for an algorithmic test set. The assessment of "equivalence" is based on established engineering principles, regulatory standards, and comparison to the predicate device, not on expert consensus for data labeling.

4. Adjudication Method for the Test Set

Since there is no "test set" in the context of an AI/ML algorithm requiring ground truth, there is no adjudication method described.

5. Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study

There is no mention of an MRMC comparative effectiveness study. This type of study is relevant for evaluating the impact of AI assistance on human reader performance, which is not applicable to an introducer system.

6. Standalone (Algorithm Only) Performance Study

This is for a physical medical device, not an algorithm. Therefore, no standalone (algorithm only) performance study was conducted or is relevant here.

7. Type of Ground Truth Used

For this type of device, the "ground truth" for demonstrating safety and effectiveness would be based on:

• Engineering specifications and standards: The device meeting its design requirements and relevant medical device standards.
• Biocompatibility testing: Demonstrating the materials are safe for human contact.
• Sterilization validation: Ensuring the device is sterile.
• Performance testing: Bench testing to confirm mechanical properties and functionality.
• Comparison to predicate device: The predicate device serves as the established "truth" of what is safe and effective in the market.

There is no "ground truth" in the AI/ML sense (e.g., pathology, outcomes data, expert consensus on imaging) for this device classification.

8. Sample Size for the Training Set

As this is not an AI/ML device, there is no "training set" sample size mentioned.

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

Not applicable, as this is not an AI/ML device.

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