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The Medyssey Co, Ltd. Iliad and Zenius Spinal Systems are intended for posterior, noncervical pedicle fixation as an adjunct to fusion in skeletally mature patients using autograft 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): spinal stenosis; curvatures (i.e., scoliosis, kyphosis, and / or lordosis); tumor; pseudoarthrosis; and failed previous fusion.

The Iliad™ Spinal Fixation and Adjustable Bridge System, Internal Fixation Device for Spinal Surgery is comprised of: Rods, Pedicle Screw Assemblies, Compression Retaining Assemblies, and Transverse-Link Assemblies. Various forms and sizes of these implants are available so that adaptations can be utilized to take into account the unique pathology of individual patients.

The Zenius™ Spinal System, Internal Fixation Device for Spinal Surgery is comprised of: Rods, Pedicle Screw Assemblies, Compression Retaining Assemblies, and Transverse-Link Assemblies. Various forms and sizes of these implants are available so that adaptations can be utilized to account for the unique pathology of individual patients.

Subject rod connectors are manufactured from Ti6Al4V ELI per ASTM F136. The subject of this submission is the addition of hook type rod connectors to the Iliad™ and Zenius™ Systems.

This is a medical device application for a spinal screw system, not an AI/ML powered device. As such, the requests for specific AI/ML study information (like sample size for test/training sets, data provenance, number/qualifications of experts for ground truth, adjudication methods, MRMC studies, or standalone algorithm performance) are not applicable to this document. The document describes a traditional medical device (pedicle screw system) and its performance testing to demonstrate substantial equivalence to a predicate device.

Here's the relevant information from the provided text, focused on the device's acceptance criteria and the study proving it, as much as possible given the nature of the device:

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

Explanation: For a mechanical device like a pedicle screw system, "acceptance criteria" are typically related to meeting established mechanical and material standards, and demonstrating equivalent performance to a legally marketed predicate device. The document explicitly states the objective was to show substantial equivalence through mechanical testing according to a specific ASTM standard.

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

• Sample Size: Not explicitly stated in terms of a "test set" as would be for AI/ML. For mechanical testing, samples refer to the physical devices tested. The document does not specify the number of devices tested.
• Data Provenance: Not applicable in the context of clinical data provenance. The "data" here refers to mechanical test results of physical devices.

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. This is not an AI/ML diagnostic or prognostic device requiring expert-established ground truth from clinical cases. The "ground truth" for a mechanical device is adherence to engineering standards and performance specifications.

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

• Not applicable. This is not an AI/ML diagnostic or prognostic device requiring adjudication of expert interpretations.

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 prognostic device.

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

• Not applicable. This is not an AI/ML algorithm.

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

• The "ground truth" equivalent for this device is the performance observed under established mechanical testing standards (ASTM F1798-13), demonstrating that the device's mechanical properties are equivalent to the predicate devices.

8. The sample size for the training set

• Not applicable. This is not an AI/ML device, so there is no "training set."

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

• Not applicable. There is no training set for a mechanical device.

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