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GS Medical's Pegasus-X Expandable PLIF System is indicated for use with autogenous bone graft in skeletally mature patients with degenerative disc disease (DDD) of the lumbar spine at one or two contiguous spinal levels from L2-S1. DDD is defined as discogenic pain with degeneration of the disc confirmed by patient history and radios. These patients should have had six months of non-operative treatment. These DDD patients may have up to Grade 1 spondylolisthesis at the involved level(s). The Pegasus-X Expandable PLIF Cage is to be combined with internal supplemental fixation cleared for use in the lumbar spine.

The Pegasus-X Expandable PLIF Cage devices are designed for restoring the height of the intervertebral space after resection of the disc. The Pegasus-X Expandable PLIF Cage devices consist of implants in various heights, footprints, and lordotic configurations with architecture designed to accept pre and post packing of bone graft material. The intervertebral body devices are made of titanium alloy (Ti-6AL-4V ELI). The Pegasus-X Expandable PLIF Cage devices are not radio lucent but have large windows through the sides that will allow visualization of the placement and subsequent bone fusion. The Expandable PLIF Cage (Posterior Lumbar Interbody Fusion Cage) are designed for segments L2 to S1.

The provided text is a 510(k) summary for the Pegasus-X Expandable PLIF System, a medical device for spinal fusion. It focuses on demonstrating substantial equivalence to already cleared predicate devices.

Crucially, this document does NOT contain information about acceptance criteria or a study proving the device meets those criteria in the context of an AI/ML-based medical device performance study.

The "Performance Data" section solely refers to mechanical and biomechanical testing of the physical implant itself (e.g., static and dynamic compression, expulsion, subsidence testing) against ASTM standards, not clinical performance or AI/ML algorithm performance.

Therefore, I cannot provide the requested information based on the given text.

To address your query regarding acceptance criteria and a study proving an AI/ML device meets them, the document would need to describe:

• Clinical performance metrics: Such as sensitivity, specificity, accuracy, F1-score, AUC for a diagnostic AI, or an effect size for an MRMC study if it's an AI-assisted tool.
• A clinical study design: Whether prospective or retrospective, the patient population, image acquisition protocols, and how ground truth was established for AI model evaluation.
• Details about the dataset: Sample size, data provenance (e.g., types of medical images, where they came from), and how it was split into training and test sets.
• Expert ground truth establishment: Number and qualifications of experts, and their adjudication methods.

Without such information, any attempt to answer your questions would be speculative and incorrect based only on the provided text.

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