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The SMG Anterior Cervical Plate System is intended for anterior screw fixation to the cervical spine (C2-C7). The System is indicated for use in the immobilization of the spine as an adjunct to fusions in patients with:

· degenerative disc disease (as defined by neck pain of discogenic origin with

degeneration of the disc confirmed by patient history and radiographic studies),

• · spondylolisthesis,
• · trauma (i.e. fractures or dislocations),
• tumors.
• · deformity (defined as kyphosis, lordosis, or scoliosis),
• · failed previous fusion (pseudoarthrosis)
• · spinal stenosis.

The SMG Anterior Cervical Plate System is composed of plates, screws and lockers which are made from titanium alloy Ti-6Al-4V ELI (ASTM F136). These plates attach to the anterior cervical spine with a minimum of four screws per plate. The plates are offered in one-level, two-level, three-level, four-level fusion configurations (13~97mm). The plate screws are 3.5mm and 4.0mm diameter head screws. They are self-tapping and selfdrilling threaded. This device is provided as non-sterile.

This is a 510(k) premarket notification for a medical device, the SMG Anterior Cervical Plate System. This type of submission focuses on demonstrating substantial equivalence to a legally marketed predicate device, rather than proving novel clinical effectiveness through extensive studies with detailed acceptance criteria as one might find for a PMA or de novo submission for a novel AI/ML device.

Therefore, the information you've requested regarding acceptance criteria for device performance in a clinical setting, sample sizes for test and training sets, expert qualifications, and adjudication methods (typical of AI/ML device evaluations) is not present in this document.

Here's an analysis based on the provided text, addressing what information is available:

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

The document does not provide specific quantitative "acceptance criteria" for clinical performance that would typically be seen for an AI/ML device. Instead, the acceptance is based on demonstrating substantial equivalence to predicate devices through a comparison of technological characteristics and performance data.

The "reported device performance" is in the context of bench testing:

2. Sample size used for the test set and the data provenance

This information is not applicable/not provided. The assessment for this device is based on mechanical bench testing and comparison to existing predicate devices, not clinical data sets or test sets as would be used for an AI/ML device.

3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts

This information is not applicable/not provided. Ground truth in the context of expert review for clinical performance is not part of this 510(k) submission.

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

This information is not applicable/not provided. Adjudication methods are relevant for clinical studies with subjective interpretation, which is not the basis of this 510(k).

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

This information is not applicable/not provided. The device is a physical anterior cervical plate system, not an AI-assisted diagnostic tool.

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

This information is not applicable/not provided. The device is a physical implant, not an algorithm.

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

This information is not applicable/not provided. The "ground truth" equivalent for this type of device is its ability to meet engineering specifications and withstand mechanical forces, as demonstrated through bench testing and comparison to established predicate devices.

8. The sample size for the training set

This information is not applicable/not provided. Training sets are relevant for AI/ML models, not for physical medical implants like an anterior cervical plate system.

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

This information is not applicable/not provided.

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