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The Arthrex BioComposite GraftBolt is intended to be used for fixation of tissue including ligament or tendon to bone and bone tendon bone during cruciate ligament reconstruction procedures.

The Arthrex BioComposite GraftBolt consists of a pre-packaged mating sheath and a screw pair offered in various sizes.

The provided document is a 510(k) summary for a medical device (Arthrex BioComposite GraftBolt) and not a study report about AI/ML device performance. Therefore, most of the requested information (acceptance criteria for AI, sample sizes for test/training sets, expert ground truth, MRMC studies, standalone performance, etc.) is not applicable to this document.

However, I can extract the relevant information regarding the device acceptance criteria and the type of study performed to demonstrate substantial equivalence, based on the provided text.

Here's the closest interpretation of your request using the given document:

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

Note: The document states that "Any differences between the BioComposite GraftBolt and the predicate devices are considered minor and do not raise questions concerning safety and effectiveness" and that "The submitted degradation and biomechanical testing data demonstrates that the ultimate load strength of the proposed devices meets or exceeds the minimum acceptance criteria." It does not, however, specify the numerical values of these minimum acceptance criteria or the exact reported ultimate load strength of the proposed device.

2. Sample sized used for the test set and the data provenance (e.g. country of origin of the data, retrospective or prospective)

This information is not applicable as the document describes a submission for a physical medical device (bone fixation screw), not an AI/ML device. The "test set" in this context would refer to the samples of the device used for biomechanical and degradation testing, but the sample size is not specified.

3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts (e.g. radiologist with 10 years of experience)

This information is not applicable as the document is about a physical medical device. Ground truth as typically understood for AI/ML devices is irrelevant here.

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

This information is not applicable.

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

This information is not applicable as the document is about a physical medical device, not an AI-assisted diagnostic tool involving human readers.

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

This information is not applicable as the document is about a physical medical device, not an AI algorithm.

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

This information is not applicable as the document is about a physical medical device. The "ground truth" for a physical device is its physical and mechanical properties, which are measured through standardized tests.

8. The sample size for the training set

This information is not applicable.

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

This information is not applicable.

Summary of the study conducted (as per the document):

The "study" referenced in this 510(k) submission is a series of degradation and biomechanical testing conducted on the Arthrex BioComposite GraftBolt. This testing was performed to demonstrate that the proposed device's ultimate load strength meets or exceeds the minimum acceptance criteria and to support its substantial equivalence to predicate devices (Arthrex Tibial GraftBolt, Arthrex BioComposite Transfix, and Arthrex BioComposite Interference Screws). The primary focus of the submission is to show that the new device, a line-extension using an existing biocomposite material, is equivalent in terms of safety and effectiveness to previously cleared devices.

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