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Non-inflammatory degenerative joint disease including osteoarthritis and avascular necrosis.
Rheumatoid arthritis.
Correction of functional deformity.
Treatment of non-union, femoral neck fracture, and trochanteric fractures of the proximal femur with head involvement, unmanageable using other techniques.
Revision of previously failed total hip arthroplasty.
Cemented and Uncemented Applications

Biomet Manufacturing Corp. is modifying the manufacturing process of ultra-high molecular weight polyethylene (UHMVPE) used in the fabrication of polyethylene acetabular components. The modified manufacturing process results in a higher cross-linked UHMWPE. The highly cross-linked UHMWPE is infused with medical grade Vitamin E.

The provided text is a 510(k) summary for the Biomet Vitamin E Acetabular Liners (E-Poly™). It is a premarket notification for a medical device seeking clearance from the FDA, not a study describing acceptance criteria and device performance. Therefore, most of the requested information cannot be extracted from this document, as it pertains to clinical trial design and results, which are explicitly stated as "None provided as a basis for substantial equivalence."

This document focuses on demonstrating substantial equivalence to previously marketed devices (predicates) based on manufacturing process modifications and non-clinical testing. It does not contain information about acceptance criteria, human reader performance, or detailed study designs typically found in a clinical trial report.

Here's what can be extracted based on the input text:

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

• Acceptance Criteria: Not explicitly stated in terms of quantitative performance metrics for a clinical study. The summary focuses on demonstrating that the modified manufacturing process for the UHMWPE liners, infused with Vitamin E, results in a "higher cross-linked polyethylene" that is safe and effective and supports the "proposed wear claims" by showing substantial equivalence to predicate devices.
• Reported Device Performance: The document states that "Non-clinical laboratory testing was performed to determine substantial equivalence. The results indicated that the device was functional within its intended use." No specific performance metrics (e.g., accuracy, sensitivity, specificity, or wear rates) are provided in this summary.

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

• Sample Size for Test Set: Not applicable. The document explicitly states "Clinical Testing: None provided as a basis for substantial equivalence." Non-clinical testing was performed, but no details on sample size for these tests are provided.
• Data Provenance: Not applicable for clinical data. For non-clinical testing, no specific details on data provenance are given.

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

• Not applicable. No clinical testing or expert evaluation for ground truth establishment is described.

4. Adjudication method for the test set:

• Not applicable. No clinical testing is described.

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 a medical device (hip implant component), not an AI-assisted diagnostic tool. No MRMC study was conducted or is relevant.

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

• Not applicable. This is a medical device, not an algorithm.

7. The type of ground truth used:

• Not applicable for clinical ground truth. For non-clinical testing, the "ground truth" would be established by standard engineering and material science testing methods and specifications, which are not detailed in this summary. The basis for substantial equivalence relies on material properties and wear claims supported by non-clinical testing results.

8. The sample size for the training set:

• Not applicable. No machine learning training set is mentioned.

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

• Not applicable. No machine learning training set is mentioned.

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