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This device is indicated for:

• Moderate to severe knee instability
• Significant bone loss and/or ligament deficiencies caused by neoplasms, trauma, rheumatoid arthritis, osteoarthritis, traumatic arthritis, polyarthritis, collagen disorders, and/or avascular necrosis of the proximal and/or proximal tibia
• Valgus, varus or flexion deformities
• The salvage of previously failed surgical attempts
• A total femoral replacement consisting of Segmental proximal femoral, Segmental System segments and Segmental System distal femoral components may be used without cement.
• Variable Stiffness stem extensions require the use of either a smooth or Trabecular Metal stem collar, which must be cemented to the stem. Following cementing to the stem, the smooth collar must be cemented against the bone. The remainder of the stem must be used uncemented.
• Fluted stem extensions require the use of either a smooth or Trabecular, which must be cemented to the stem. Following cementing to the stem extension, the smooth collar must be cemented against the bone. The remainder of the stem must also be cemented against the bone.
• The Trabecular Metal collar may be used cemented or uncemented against the bone.
• All other constructs are for cemented use only.

The subject devices are intended for use in limb salvage arthroplasty.

This FDA 510(k) summary for the Zimmer® Segmental System does not describe a study involving a test set, expert ground truth, or an acceptance criteria table for device performance in the sense of an AI/ML or diagnostic imaging device determining a clinical outcome.

Instead, the document details a premarket notification for a knee and hip prosthesis system. The "performance data" section focuses on non-clinical tests to ensure the device's safety, compatibility (especially in an MRI environment), and mechanical integrity. It explicitly states that no clinical data was provided for the subject devices.

Therefore, most of the requested information regarding ground truth, expert consensus, MRMC studies, standalone performance, and training sets is not applicable to this submission.

However, I can extract the information that is present related to the "acceptance criteria" and "study" proving the device's adherence to safety and performance standards for a medical implant like this.

Here's a breakdown based on the provided text:

Acceptance Criteria and Device Performance for Zimmer® Segmental System (K192798)

This submission focuses on demonstrating the safety and effectiveness of the Zimmer® Segmental System as a knee and hip prosthesis, primarily through non-clinical testing and comparison to predicate devices, rather than through a clinical performance study with human subjects or an AI algorithm.

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

The document doesn't provide a quantitative "acceptance criteria" table in the format of precision, recall, or accuracy for a diagnostic device. Instead, the acceptance is based on meeting established standard test methods and internal criteria for the physical and material properties of the implant, especially regarding safety in an MRI environment and mechanical integrity.

Conclusion on Substantial Equivalence: "Non-clinical tests provided in this Traditional 510(k) establish the conditional safety and compatibility of the passive implants in a magnetic resonance (MR) environment, as well as any differences do not raise new questions of safety and effectiveness. The subject devices are substantially equivalent to the legally marketed predicated devices."

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

• Sample Size: The document does not specify quantitative sample sizes for each non-clinical test (e.g., number of implant samples tested for fatigue). These are typically determined by the requirements of the specific ASTM or ISO standard applied.
• Data Provenance: The tests were non-clinical (laboratory/engineering tests) performed by Zimmer, Inc. The document does not specify a country of origin for the internal testing data, but the company is based in Warsaw, Indiana, USA. The data is prospective in the sense that these tests were conducted specifically for this 510(k) submission.

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

Not applicable in the context of this device. "Ground truth" for an implant device is established through meeting material specifications, standardized mechanical performance, and biocompatibility requirements. This involves engineering and scientific expertise (materials scientists, mechanical engineers, etc.) in designing and testing the device, and regulatory experts validating compliance with standards, rather than clinical experts establishing a "ground truth" on patient outcomes for a test set.

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

Not applicable. Adjudication methods are relevant for clinical studies or studies using human readers/interpreters where disagreements need to be resolved. This submission relies on objective, repeatable non-clinical laboratory test results.

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/ML or diagnostic imaging device. No MRMC study was conducted.

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

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

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

For this type of device, the "ground truth" is defined by:

• Compliance with recognized industry standards (e.g., ASTM, ISO standards for MRI safety, biocompatibility, packaging).
• Demonstration of mechanical properties (e.g., fatigue strength, stress analysis) meeting design specifications necessary for intended use.
• Material properties meeting specified requirements (e.g., specific metal alloys, polymers).
• Demonstration that the manufacturing process consistently produces devices meeting these specifications (e.g., endotoxin limits).

These are validated through established laboratory test methods and engineering principles.

8. The sample size for the training set

Not applicable. This device does not use a "training set" in the context of machine learning or AI.

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

Not applicable. (See #8)

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