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The Evolis®/GMK® knee prosthesis is designed for cemented use in total knee arthroplasty, if there is evidence of sufficient sound bone to seat and support the components.

This knee replacement system is indicated in the following cases:

• · Severely painful and/or disabled joint as a result of arthritis, traumator arthritis, theumatord arthritis.
• Avascular necrosis of femoral condyle.
• · Post traumatic loss of joint configuration.
• · Primary implantation failure.

Tibial wedges cemented are to be attached to the tibial baseplate with both the fixing cylinders and bone cement. The screwed tibial augments are for screwed fixation to the tibial baseplate. In case a semi-constrained liner is used, an extension stem must be implanted both on the tibial and on the femoral components. In case a GMK Revision or GMK Sphere Revision tibial tray is used, an extension stem must be implanted.

The GMK Sphere Revision is a Medacta GMK line extension to provide a larger product offering. The subject devices are designed for cemented use in total knee arthroplasty procedures. The GMK Sphere Revision system includes:

• Femoral components, left and right, sizes from 2 to 8, with or without TiNbN coating; ●
• . Tibial trays, left and right, sizes T3I4 and T4I3, with or without TiNbN coating;
• Distal wedges, 4 sizes (2, 3-4, 5-6, 7-8) with thicknesses 4, 8, 12, 16 and 20 mm; ●
• Posterior wedges, 6 sizes (2, 3-4, 5, 6, 7, 8) with thicknesses 4, 8 and 12 mm; ●
• Offset connectors from 2 to 5 mm. ●

The GMK Sphere Revision implants, both femoral components and tibial trays, are manufactured from cobalt-chromium-molybdenum alloy (Co-Cr-Mo) according to ISO 5832-4 and they are available with or without Titanium Niobium Nitride (TiNbN) coating.

The GMK Sphere Revision wedges and offset connectors, are manufactured from Ti6A14V per ISO 5832-3.

The provided document describes a 510(k) premarket notification for a medical device, specifically a knee prosthesis called "GMK Sphere Revision." This type of submission focuses on demonstrating substantial equivalence to a legally marketed predicate device, rather than proving the device meets specific performance criteria through extensive clinical studies as one might find for novel AI/ML devices or high-risk devices.

Therefore, the information you've requested regarding acceptance criteria, study details, expert involvement, and ground truth establishment, as typically associated with the development and validation of sophisticated medical software or AI/ML algorithms, is largely not present in this document. This document emphasizes non-clinical performance testing to show the new device (GMK Sphere Revision) is comparable to existing predicate devices, rather than an AI/ML system proving its diagnostic accuracy against human experts or a gold standard.

Here's how to interpret the available information concerning your request, and where the requested details are not applicable or not provided:

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

• Acceptance Criteria: Not explicitly stated as pass/fail metrics for clinical outcomes or diagnostic accuracy. Instead, the "acceptance criteria" are implicitly met by demonstrating that the device's technical characteristics and performance in non-clinical tests are comparable to the predicate devices and meet relevant ISO and ASTM standards for biomechanical properties, wear, and material safety.
• Reported Device Performance: Instead of specific performance numbers against clinical metrics, the document lists the types of non-clinical tests performed. The implication is that the device passed these tests and exhibited performance comparable to the predicate.

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

• Test Set (for performance testing): For a medical device like a knee prosthesis, "test set" refers to the physical samples of the device components used for biomechanical and material testing. The document does not specify the number of samples used for each non-clinical test.
• Data Provenance: Not applicable in the context of clinical data for this type of submission. The tests are benchtop, in-vitro, or material characterization tests.

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

• Not Applicable. This document is for a traditional medical device (implantable prosthesis), not an AI/ML diagnostic system that requires expert ground truth labeling of patient data.

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

• Not Applicable. Adjudication methods are relevant for human reader studies or expert consensus for AI/ML ground truth, neither of which are described here.

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:

• No. This is a 510(k) for a physical implant, not an AI-assisted diagnostic or imaging device. Therefore, MRMC studies and AI assistance comparisons are not relevant and were not performed.

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

• Not Applicable. This is not an algorithm-based device.

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

• Not Applicable. For the non-clinical tests, the "ground truth" is defined by the accepted and validated methodologies of the ISO and ASTM standards themselves (e.g., how much force a component can withstand, how much wear occurs under specified conditions, etc.). There is no clinical "ground truth" such as pathology or outcomes data presented here.

8. The sample size for the training set:

• Not Applicable. This is not an AI/ML device that requires a training set.

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

• Not Applicable. As above, no training set for an algorithm is involved.

In summary, the provided FDA 510(k) clearance letter and its summary are for a conventional orthopedic implant. The substantial equivalence pathway for such devices primarily relies on demonstrating that the new device has the same intended use, technological characteristics, and comparable performance (through non-clinical bench testing) to a predicate device. It does not involve the types of studies, ground truth establishment, or expert-based evaluations typically associated with AI/ML-driven medical devices.

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