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The MILAGRO Interference Screw is indicated for the fixation of soft tissue grafts or bone-tendon-bone grafts during cruciate ligament reconstruction surgeries of the knee. Additionally, the 7, 8 and 9 mm x 23 mm screws will be indicated for medial and lateral collateral ligament repair of the knee, proximal bicep tenodesis in the shoulder and distal bicep tenodesis in the elbow.

The MILAGRO Interference Screw is a cannulated, threaded, tapered fastener for use in interference fixation of soft tissue grafts or bone-tendon-bone grafts. The device is made from a copolymer of absorbable Poly(lactide-co-glycolide) (PLA PGA) compounded with beta-Tricalcium Phosphate (beta-TCP) and is available in several sizes and varied lengths.

The provided text describes a 510(k) summary for the MILAGRO Interference Screw. This document is a premarket notification to the FDA to demonstrate that the device is substantially equivalent to legally marketed predicate devices. It focuses on the safety and performance of the device through non-clinical laboratory testing.

1. Table of Acceptance Criteria and Reported Device Performance:

The document explicitly states that "Non-clinical laboratory testing was performed demonstrating that the device is safe and can be considered substantially equivalent to the predicate devices for the proposed new intended uses." However, it does not provide a specific table of acceptance criteria or detailed reported device performance metrics (e.g., tensile strength, degradation rates, biocompatibility test results, etc.). It only mentions that the device is made from a copolymer of absorbable Poly(lactide-co-glycolide) (PLA PGA) compounded with beta-Tricalcium Phosphate (β-TCP).

Therefore, a table cannot be constructed from the provided text as the specific criteria and corresponding performance values are not detailed.

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

The document mentions "Non-clinical laboratory testing" but does not specify the sample sizes used for these tests. There is no information regarding the data provenance (e.g., country of origin, retrospective or prospective) as it pertains to laboratory testing data, not human patient data.

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

Since the testing described is "non-clinical laboratory testing" and not related to clinical image interpretation or diagnosis, the concept of "experts establishing ground truth" in the traditional sense of medical image analysis does not apply here. The document does not mention any experts or their qualifications for establishing ground truth.

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

As this is non-clinical laboratory testing and not a clinical study involving interpretation or diagnosis, an adjudication method for a "test set" is not relevant and is not mentioned in the document.

5. If a multi-reader multi-case (MRMC) comparative effectiveness study was done:

No, an MRMC comparative effectiveness study was not done or mentioned. The safety and performance were based on "non-clinical laboratory testing."

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

This question is not applicable. The device is a physical interference screw, not an algorithm or AI. Therefore, a "standalone algorithm performance" study was not conducted.

7. The type of ground truth used:

For "non-clinical laboratory testing," the ground truth would be established by physical measurements and analytical results according to established scientific and engineering standards (e.g., material properties testing, mechanical strength testing, degradation studies, biocompatibility assays). The document does not specify the exact type of physical or chemical ground truth used beyond stating "non-clinical laboratory testing."

8. The sample size for the training set:

As this is non-clinical laboratory testing for a physical medical device, there is no concept of a "training set" as would be used in machine learning or AI.

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

This question is not applicable due to the reasons stated in point 8.

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