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This device is indicated for patients with severe knee pain and disability due to:

• Rheumatoid arthritis, osteoarthritis, traumatic arthritis, polyarthritis.
• Collagen disorders, and/or avascular necrosis of the femoral condyle.
• Post-traumatic loss of joint configuration, particularly when there is patellofemoral erosion, dysfunction or prior patellectomy
• Moderate valgus, varus, or flexion deformities.
• The salvage of previously failed surgical attempts or for a knee in which satisfactory stability in flexion cannot be obtained at the time of surgery.
  The device is indicated for use when both cruciate ligaments have been excised.
  The device is intended for use as part of a cemented or uncemented knee prosthesis.

The NexGen LPS-Flex Prolong articular surfaces are part of the NexGen system of semiconstrained,

The provided document describes a 510(k) premarket notification for a medical device, specifically NexGen® Complete Knee Solution LPS-Flex Prolong™ Highly Crosslinked Polyethylene Articular Surfaces. The document focuses on demonstrating substantial equivalence to predicate devices rather than a de novo study with explicit acceptance criteria and performance data.

Therefore, many of the requested categories (2-9) are not directly applicable or explicitly stated in this type of submission which primarily relies on equivalence to devices already on the market.

Here's an analysis based on the provided text:

1. Table of Acceptance Criteria and Reported Device Performance

The submission is a 510(k), which asserts substantial equivalence to predicate devices rather than establishing new performance acceptance criteria and showing performance against them in a de novo study. The "Performance Data" section explicitly states "Non-Clinical Performance and Conclusions: Performance testing completed as part of the design assurance process demonstrated that this device is safe and effective and substantially equivalent to the predicate device. Clinical Performance and Conclusions: Clinical data and conclusions were not needed for this device."

Therefore, a table of explicit acceptance criteria and reported device performance, as one would see in a de novo study, is not provided in this type of submission. The 'acceptance criterion' for a 510(k) is demonstrating substantial equivalence to a legally marketed predicate. The 'performance' is therefore inherently linked to the performance of the predicate device.

2. Sample Size Used for the Test Set and Data Provenance

Not applicable. No dedicated "test set" or clinical study with a prospectively collected sample size is described as clinical data was not needed. The non-clinical performance refers to design assurance testing, which would typically involve laboratory testing, not a clinical test set. The provenance of such non-clinical data would be internal lab reports.

3. Number of Experts Used to Establish Ground Truth for the Test Set and Qualifications

Not applicable. As clinical data and a test set requiring ground truth establishment by experts were not needed or presented, this information is not provided.

4. Adjudication Method for the Test Set

Not applicable. No test set requiring expert adjudication is described.

5. Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study

Not applicable. No clinical study, let alone an MRMC study comparing human readers with or without AI assistance, was performed or presented for this 510(k) submission.

6. Standalone (Algorithm Only Without Human-in-the-Loop Performance) Study

Not applicable. This device is a physical knee prosthesis component, not an algorithm or AI. Therefore, a standalone performance study in the context of an algorithm's performance is not relevant.

7. Type of Ground Truth Used

Not applicable, as no external "ground truth" for a clinical assessment was required. The "truth" in this context is established through engineering and material science testing that demonstrates the physical properties and performance characteristics (e.g., wear, strength) of the device are equivalent to the predicate.

8. Sample Size for the Training Set

Not applicable. This device is not an AI/ML algorithm that requires a training set.

9. How the Ground Truth for the Training Set Was Established

Not applicable. As this is not an AI/ML device, there is no training set or ground truth in that context.

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