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The TTC Phantom® Intramedullary Nail system is intended for tibiotalocalcaneal arthrodesis (fusion) and to provide stabilization of the hindfoot and ankle including the transverse tarsal joints coupling the mid-foot to the hindfoot. Examples of specific indications include:

• Post-traumatic or degenerative arthritis
• Previously infected arthrosis
• Revision of failed ankle arthrodesis
• Revision of failed total ankle arthroplasty
• Talar deficiency conditions such as avascular necrosis of the talus (requiring tibiocalcaneal arthrodesis)
• Neuromuscular deformity or other neuromuscular disease with severe deformity or instability of the ankle
• Rheumatoid arthritis
• Osteoarthritis
• Nonunions or pseudarthrosis of hindfoot and distal tibia
• Trauma (severe or malunited tibial pilon fracture)
• Charcot foot (neuroarthropathy)
• Severe end-stage degenerative arthritis
• Instability and skeletal defects after tumor resection
• Pantalar arthrodesis
• Severe foot/ankle deformity

The Paragon 28® TTC Phantom® Intramedullary Nail System is comprised of intramedullary nails, screws and accessory components. The TTC Phantom® nails are offered in a variety of sizes and lengths to accommodate variations in patient anatomy. The TTC Phantom® screws insert through the intramedullary nail to secure the construct. These are offered in varying lengths to accommodate the anatomical fixation required.

This is for the approval of a physical medical device (TTC Phantom® Intramedullary Nail System), not a medical AI device. Therefore, much of the requested information (like sample size for test/training sets, data provenance, ground truth establishment, MRMC studies, standalone performance, etc.) is not applicable here as these concepts are specific to the evaluation of AI/ML models.

However, I can provide information based on the provided text regarding the closest equivalent to acceptance criteria and the study performed for this physical device.

Acceptance Criteria and Device Performance (Closest Equivalent for a Physical Device)

Study Information (Based on Physical Device Evaluation):

1. Sample size used for the test set and the data provenance: Not applicable in the context of AI/ML model evaluation. For this physical device, the "test set" would refer to the components undergoing engineering analysis and cadaveric implantation. The text does not specify the number of components or cadavers used, nor their specific provenance.

2. Number of experts used to establish the ground truth for the test set and the qualifications of those experts: Not applicable. Ground truth for a physical device like an intramedullary nail is established through engineering principles, material testing standards, and mechanical performance evaluation rather than subjective expert consensus on data interpretation.

3. Adjudication method for the test set: Not applicable for a physical device evaluation. Adjudication methods are typically employed in studies where multiple human readers interpret data that may have ambiguous findings, which is not the case for material and mechanical performance testing.

4. 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 for a physical medical device, not an AI product.

5. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done: Not applicable. This is for a physical medical device.

6. The type of ground truth used:

   • Engineering analysis: This implies adherence to established engineering principles and standards for material strength, durability, and biomechanical function.
   • Cadaveric implantation study: This provides practical, real-world (though ex-vivo) evidence of how the device performs within a biological context, assessing fit, stability, and potential issues during implantation.
   • The "ground truth" here is the objective measurement of mechanical properties and functional performance against established benchmarks and predicate device performance.

7. The sample size for the training set: Not applicable. This is for a physical medical device. The "training" for such a device involves design iterations, material selection, and manufacturing process optimization, not algorithm training data.

8. How the ground truth for the training set was established: Not applicable. For a physical device, continuous improvement and design validation are ongoing processes. The basis for design decisions and material choices would come from established engineering and medical device standards, previous product performance, and clinical needs.

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