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The AEGIS Anterior Lumbar Plate System is indicated for use as an anteriorly placed supplemental fixation device via the lateral or anterolateral surgical approach above the bifurcation of the great vessel or via the anterior surgical approach, below the bifurcation of the great vessels.

The device is intended as a temporary fixation device until fusion is achieved. The AEGIS Anterior Lumbar Plate System is intended for anterior lumbar (L1 - S1) fixation for the following indications: degenerative disc disease (DDD) (defined as back pain of discogenic origin with degeneration of the disc confirmed by history and radiographic studies), spondylolisthesis, trauma (i.e., fracture or dislocation), deformities or curvatures (i.e., scoliosis, kyphosis, and/or lordosis), tumor, pseudoarthrosis, and failed previous fusion.

The AEGIS Anterior Lumbar Plate System consists of an assortment of plates and screws.

The AEGIS Anterior Lumbar Plate System also contains Class 1 manual surgical instruments and cases that are considered exempt from premarket notification.

This document describes the regulatory submission for the AEGIS Anterior Lumbar Plate System, a medical device. It does not contain information about a study proving the device meets acceptance criteria in the context of AI/ML performance.

The provided text is a 510(k) summary for a spinal implant system, which focuses on device description, intended use, materials, and substantial equivalence to predicate devices, rather than performance as would be measured for AI/ML systems. Therefore, most of the requested information regarding AI/ML study design, sample sizes, ground truth establishment, expert qualifications, and MRMC studies is not applicable to this document.

However, I can extract the information provided about the performance data and the type of evaluation conducted for this medical device:

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

The document states: "Performance data were submitted to characterize the AEGIS Anterior Lumbar Plate System components."

Without the actual performance data or explicit acceptance criteria from the 510(k) submission, a detailed table cannot be created. For a mechanical implant like this, "acceptance criteria" generally refer to specific mechanical testing standards (e.g., fatigue strength, torsional rigidity) that the device must meet, and "reported device performance" would be the results of those tests. The 510(k) process primarily relies on demonstrating substantial equivalence to predicate devices, often through mechanical testing to show similar performance characteristics.

2. Sample sized used for the test set and the data provenance (e.g. country of origin of the data, retrospective or prospective):

Not applicable. This is a medical device (spinal implant) approval, not an AI/ML diagnostic or predictive device. The "test set" in this context would refer to mechanical test specimens, and not a dataset of patient information. The document does not specify the number of test specimens or the provenance of the material testing data, but it is implied to be laboratory-based testing of the device components.

3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts (e.g. radiologist with 10 years of experience):

Not applicable. "Ground truth" in the context of this device's approval would relate to established engineering principles, material science standards, and the performance of predicate devices, not expert consensus on diagnostic interpretations.

4. Adjudication method (e.g. 2+1, 3+1, none) for the test set:

Not applicable. Adjudication methods are relevant for subjective evaluations, typically in clinical studies or AI/ML ground truth establishment, neither of which are detailed in this 510(k) summary for a mechanical device.

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:

Not applicable. This is not an AI-assisted diagnostic or therapeutic device.

6. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done:

Not applicable. This is a physical medical implant, not an algorithm.

7. The type of ground truth used (expert consensus, pathology, outcomes data, etc.):

For a mechanical device like this, the "ground truth" for demonstrating performance usually comes from:

• Mechanical testing standards: Compliance with established ASTM or ISO standards for spinal implants (e.g., fatigue, static strength).
• Material properties: Verification that the materials used (ASTM F-136 implant grade titanium alloy) meet published specifications.
• Predicate device comparison: Performance is often compared against legally marketed predicate devices to establish substantial equivalence.

8. The sample size for the training set:

Not applicable. This is not an AI/ML device requiring a training set.

9. How the ground truth for the training set was established:

Not applicable. This is not an AI/ML device requiring a training set.

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