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The JuggerStitch Meniscal Repair Device is indicated for repair of vertical longitudinal full thickness tears (i.e. bucket-handle) in the red-red and red-white zones. These devices are not to be used for meniscal tears in the avascular zone of the meniscus.

The JuggerStitch Meniscal Repair Device is a permanent fixation anchor system comprised of UHMWPE suture, with two non-resorbable polyester sleeves. The device comes as a unit, pre-assembled on either a Straight or Curved inserter. The purpose of this submission is to introduce modifications to the Juggerstitch suture implant and inserter for ease of use.

This document is a 510(k) Premarket Notification for the JuggerStitch Meniscal Repair Device. It primarily focuses on demonstrating substantial equivalence to a predicate device, rather than proving the device meets specific performance acceptance criteria for an AI/algorithm-driven device. As such, the information required to answer the prompt directly, especially regarding acceptance criteria for AI performance, sample sizes for test/training sets, expert adjudication, MRMC studies, or specific ground truths for an algorithm, is not present in this document.

The document discusses non-clinical tests performed to verify the physical characteristics and performance of the mechanical device due to modifications made to a previously cleared device. These include:

• Static tensile testing: To verify the strength of the implant.
• Cantilever bend testing: To verify the bending strength of the inserter needles.
• Tissue penetration force testing: To verify the penetration force of the inserter needles.
• Advancement testing: To verify the force required to advance the depth adjuster and push button.
• Surgeon validation: To assess if the device meets its intended User Needs (related to ease of use of modifications).
• Sterilization validations: To show compliance with ISO standards.
• Packaging validations: To show compliance with ISO standards.

The document explicitly states: "Clinical data was not required to establish substantial equivalence between the subject JuggerStitch Meniscal Device and the predicate devices." This confirms that there was no clinical study, let alone one involving AI or algorithms, to assess the device's performance in a diagnostic or predictive capacity.

Therefore, I cannot provide the requested table and study details as they pertain to algorithm performance and acceptance criteria. The provided text describes a submission for a mechanical meniscal repair device, not a software or AI-driven medical device.

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The JuggerStitch Meniscal Repair Device is indicated for repair of vertical longitudinal full thickness tears (i.e. buckethandle) in the red-red and red-white zones. These devices are not to be used for meniscal tears in the avascular zone of the meniscus.

The JuggerStitch Meniscal Repair Device is a permanent fixation anchor system comprised of UHMWPE suture, with two non-resorbable polyester sleeves. The device comes as a unit, preassembled on either a straight or curved inserter.

I am sorry, but the provided text does not contain the detailed information necessary to complete the table and answer all the questions regarding the acceptance criteria and the study that proves the device meets them. The document is a 510(k) summary for a medical device, the JuggerStitch Meniscal Repair Device, and primarily focuses on establishing substantial equivalence to a predicate device.

Here's what I can extract and what's missing:

1. Table of Acceptance Criteria and Reported Device Performance:

The document mentions "non-clinical laboratory testing was performed to verify the fixation strength of the JuggerStitch Meniscal Repair Device in mechanical testing as compared to the MaxFire MarXmen Meniscal Repair Device." It then states, "The test results indicate that the JuggerStitch Meniscal Repair Device provides equivalent fixation strength to the predicate device and would be functional within their intended use."

However, specific numerical acceptance criteria (e.g., minimum fixation strength in Newtons) and the exact reported performance values for both the JuggerStitch and the predicate device are not provided. Therefore, a table with specific acceptance criteria and reported performance cannot be generated from this text.

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

• Sample Size: Not specified in the document.
• Data Provenance: The document states "non-clinical laboratory testing was performed." It does not mention country of origin or whether it was retrospective or prospective, though "non-clinical laboratory testing" typically implies a controlled, prospective lab setting.

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

• Not applicable as this was non-clinical mechanical testing, not a study requiring expert clinical ground truth assessment.

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

• Not applicable as this was non-clinical mechanical testing.

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:

• No MRMC or human-in-the-loop study was mentioned. The device is a physical medical device, not an AI or imaging diagnostic tool.

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

• Not applicable as this is a physical medical device.

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

• For the non-clinical mechanical testing, the "ground truth" or reference was the fixation strength of the predicate device. The goal was to show equivalence.

8. The sample size for the training set:

• Not applicable. This document describes a non-clinical performance test for a physical device, not a machine learning model that would have training data.

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

• Not applicable.

In summary, the provided document is a 510(k) summary that focuses on demonstrating substantial equivalence through comparison to a predicate device, primarily via non-clinical mechanical testing. It does not provide the detailed quantitative data, sample sizes for mechanical testing beyond a general statement, or information on clinical studies, expert reviews, or AI performance metrics.

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