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The Biomet Microfixation Sternal Closure System is intended for use in the stabilization and fixation of fractures of the anterior chest wall including sternal fixation following sternotomy and sternal reconstructive surgical procedures, to promote fusion. The Biomet Microfixation Sternal Closure System is intended for use in patients with normal and poor bone quality.

Biomet Microfixation Sternal Closure System contains a variety of plates and 2.4mm and 2.7mm diameter self-drilling screws with maximum length of 20mm. The tip of the screw is designed so that a predrilled hole is not required, but may be used. Material: Titanium. Sterility Information: The Biomet Microfixation Sternal Closure System will be marketed as non-sterile, single use devices. Validated steam sterilization recommendations are included in the package insert.

The provided document is a 510(k) summary for the Biomet Microfixation Sternal Closure System. It is focused on demonstrating substantial equivalence to predicate devices for regulatory approval, rather than describing a clinical study with detailed acceptance criteria and performance metrics typically found in clinical trials for AI/software devices. Therefore, much of the requested information regarding acceptance criteria, sample sizes, ground truth establishment, expert qualifications, and specific study types (MRMC, standalone) is not applicable or not available in this type of regulatory submission.

The document primarily describes mechanical non-clinical testing to support the substantial equivalence claim.

Here's a breakdown of the requested information based on the provided text:

1. Table of Acceptance Criteria and Reported Device Performance

As this is a 510(k) submission based on substantial equivalence, there are no explicit "acceptance criteria" in the sense of predefined thresholds for clinical performance metrics (e.g., sensitivity, specificity) that a new AI device might have. Instead, the "performance" is demonstrated through mechanical non-clinical testing comparing the device to a predicate.

Study Proving Device Meets Acceptance Criteria:

A mechanical non-clinical testing study was performed.

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

• Test Set Sample Size: Not specified in terms of number of samples, but the testing involved a "polyurethane foam substrate" to simulate bone.
• Data Provenance: The mechanical testing was conducted using a "polyurethane foam substrate which simulates Osteoporotic bone." The article "Compressive properties of commercially available polyurethane foams as mechanical models for osteoporotic human cancellous bone" by Patel et al. is referenced as the basis for this simulation. This is a retrospective selection of a material model for testing, not real-world patient data.

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

• Not Applicable. Ground truth, in the context of diagnostic accuracy, is not relevant for this type of mechanical device testing. The "ground truth" here is the physical properties of the materials and the defined testing methodologies.

4. Adjudication Method for the Test Set

• Not Applicable. Adjudication is not relevant for mechanical device testing.

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

• No. An MRMC study is relevant for comparing diagnostic performance with and without AI assistance using human readers. This document describes a mechanical device, not a diagnostic AI system.

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

• Not Applicable. This is a hardware device, not an algorithm. The testing described is intrinsic to the device's physical properties.

7. Type of Ground Truth Used

• Physical properties and standardized test methods. The "ground truth" for this testing is the quantifiable mechanical performance (fatigue, shear force, lateral pull apart) of the device and the predicate under controlled laboratory conditions using a simulated bone substrate.

8. Sample Size for the Training Set

• Not Applicable. This is a hardware device, not an AI algorithm that requires a training set.

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

• Not Applicable. No training set was used.

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