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The AXS Lift Intracranial Base Catheter is introduction of interventional devices into the peripheral and neurovasculature.

The AXS Lift Intracranial Base Catheter ("AXS Lift") is a single lumen, variable stiffness catheter designed for use in facilitating the insertion and guidance of appropriately sized interventional devices into the peripheral and neurovasculature. The distal catheter shaft has a hydrophilic coating to reduce friction during use. The catheter includes a radiopaque marker on the distal end for angiographic visualization and a luer hub on the proximal end. The distal end of the catheter contains bovine derived tallow. It is packaged with one double port rotating hemostasis valve (RHV) and one peel-away introducer sheath. The peel-away introducer sheath is designed to protect the distal tip of the catheter during insertion into the short introducer sheath valve. The AXS Lift Intracranial Base Catheter is compatible with short introducer sheaths with an inner diameter of 7Fr or greater. AXS Lift is supplied sterile, non-pyrogenic, and is intended for single use only.

The provided text, K243593 for the AXS Lift Intracranial Base Catheter, describes the predicate device equivalence testing rather than a study proving the device meets acceptance criteria for an AI/ML algorithm. The document focuses on the mechanical and material performance of a catheter, not the performance of a software algorithm.

Therefore, the requested information regarding acceptance criteria, study design for AI/ML performance (sample size, data provenance, expert ground truth, adjudication, MRMC, standalone performance, training set details), cannot be extracted from this document as it does not contain information about an AI/enabled medical device.

The document definitively states on page 9:

"No animal or clinical study was conducted as bench testing was determined sufficient for verification and validation purposes."

This reinforces that the approval is based on physical and material device characteristics, not an AI/ML algorithm's performance on clinical data or human-in-the-loop studies.

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