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The AUDERE Lumbar Spacer System is indicated for spinal fusion procedures in skeletally mature patients with degenerative disc disease (DDD) at one or two contiguous levels in the lumbar spine (L2-S1) with up to Grade 1 spondylolisthesis or retrolisthesis at the involved level(s). DDD is defined as discogenic back pain with degeneration of the disc confirmed by history and radiographic studies. Patients with previous non-fusion spinal surgery at the involved level may be treated with the AUDERE Lumbar Spacer System.
Patients must have undergone a regimen of at least six (6) months of non-operative treatment prior to being treated with the AUDERE Lumbar Spacer System.
The AUDERE Lumbar Spacer System is designed for use with autogenous bone graft. The system is also intended to be used with supplemental fixation systems that are cleared by the FDA for use in the lumbar spine.

The AUDERE Lumbar Spacer System consists of implants and trials that are compatible with all previously cleared AUDERE instruments. The AUDERE Lumbar Spacer System may be implanted bilaterally using a posterior (PLIF) approach, or as a single device employing a transforaminal (TLIF) approach.

The provided text describes a medical device, the AUDERE Lumbar Spacer System, and its FDA 510(k) clearance (K193457). However, the document does not contain information about acceptance criteria for an AI/algorithm-based device, nor does it detail a study proving device performance in the context of AI.

This document is for a physical implantable medical device (intervertebral body fusion device), not a software or AI-driven diagnostic/treatment device. The performance data section refers to non-clinical mechanical testing (e.g., static axial compression, dynamic axial compression, expulsion, subsidence) demonstrating the physical strength and durability of the implant, not the diagnostic or analytical performance of an algorithm.

Therefore, I cannot extract the requested information regarding acceptance criteria and studies for an AI/algorithm device from the provided text. The questions about sample size, data provenance, ground truth, expert qualifications, adjudication methods, MRMC studies, or standalone algorithm performance are not applicable to this document.

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