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The Agilis HisPro Steerable Catheter With Electrodes is indicated to provide a pathway for delivery and support of transvenous devices within the chambers and vasculature of the heart and can be used for electrogram recording and stimulation.

The Agilis HisPro Steerable Catheter With Electrodes is a deflectable, slittable catheter with two distal tip electrodes. It serves as a delivery conduit for devices such as cardiac leads. The distal portion can be formed into a "U" shape, when fully deflected, to facilitate positioning of the tip at a desired location in the heart. The 10.5 Fr catheter has a braided shaft with a multi-durometer outer Pebax jacket. The catheter has a 7 Fr diameter lumen that allows for delivery of a 6Fr cardiovascular transvenous device, including a 6Fr pacing lead. The Agilis HisPro catheter's proximal handle consists of a rotating actuator with passive locking mechanism for deflecting the distal portion, a hemostasis valve for leak-proof delivery, and an integrated cable incorporating a 4-pin electrical connection for connecting to external electrical systems via a commercially available electrophysiology cable. The tip electrodes provide the ability to sense intracardiac electrogram (EGM) and pace when connected to the Merlin™ Pacing System Analyzer (PSA) or the WorkMate Claris™ Recording System. The sensing and pacing feature of the Agilis HisPro catheter provides the ability to identify the desired location in the heart. Accessories packaged for use with the Agilis HisPro catheter include dilator, guidewire for vascular access, cable adaptor pins for connection to the Merlin PSA via the electrophysiology cable, valve bypass tools for lead insertion, three-way stopcock and slitter. The catheter and the packaged accessories are provided as a sterile single-use device.

The provided FDA 510(k) summary for the Agilis HisPro Steerable Catheter With Electrodes does not contain information about a study proving the device meets specific acceptance criteria in the context of AI/machine learning or diagnostic performance metrics.

The document describes the device's technical specifications, indications for use, comparison to predicate devices, and a list of performance bench testing, packaging and shelf-life testing, biocompatibility assessment, and some animal testing. However, it does not mention:

• Acceptance criteria directly related to diagnostic performance (e.g., sensitivity, specificity, accuracy).
• Any study with a "test set" and "training set" of data, ground truth establishment, or expert adjudication that would be typical for validating an AI/ML medical device.
• Multi-reader multi-case (MRMC) comparative effectiveness studies.
• Standalone algorithm performance.

The listed tests are primarily focused on the physical, electrical, functional, and biological safety and performance of a medical catheter, not on a diagnostic or prognostic algorithm's performance.

Therefore, I cannot populate the requested table or answer the specific questions related to AI/ML device validation based on the provided text.

The information that is available relates to the overall performance testing for regulatory clearance of a physical medical device. Below is a summary of the performance testing performed, but it doesn't align with the requested format for AI/ML device performance.

Summary of Performance Testing (as described in the document):

The device underwent various performance tests to demonstrate it meets design specifications and is as safe and effective as predicate devices.

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

• The document lists categories of tests but does not provide specific numerical acceptance criteria (e.g., "deflection force must be X N ± Y N") or quantified "reported device performance" values for each criterion. It only states that testing "demonstrated that the subject device is as safe and effective as the predicate devices."

Summary of Performance Tests Performed:

Since the document does not relate to an AI/ML device, the following points cannot be addressed:

• 2. Sample sized used for the test set and the data provenance
• 3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts
• 4. Adjudication method for the test set
• 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
• 6. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done
• 7. The type of ground truth used
• 8. The sample size for the training set
• 9. How the ground truth for the training set was established

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