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The NovoStitch Pro Mensical Repair System is intended for approximation of soft tissue in meniscal repair procedures.

The NovoStitch Pro Meniscal Repair System, size 0 is a new configuration of the predicate device. While the predicate device passes size 2-0 suture, this new configuration passes size 0 braided, nonabsorbable, surgical suture through soft tissue in arthroscopic surgery. It is comprised of a handheld surgical instrument to which cartridges preloaded with suture are attached.

Here's an analysis of the provided text regarding the NovoStitch Pro Meniscal Repair System, CTX-A004 (size 0), focusing on acceptance criteria and the supporting study:

The provided document is a 510(k) summary for the NovoStitch Pro Meniscal Repair System, CTX-A004 (size 0). This document is primarily concerned with demonstrating substantial equivalence to a predicate device (NovoStitch Pro Meniscal Repair System, CTX-A003 (size 2-0)) rather than detailing a comprehensive study with specific acceptance criteria in the manner one might find for a novel AI/software device. The device in question is a surgical instrument that deploys sutures.

Therefore, the information you've requested regarding AI/software performance metrics (like sensitivity, specificity, MRMC studies, training set details, ground truth establishment for training, etc.) is not applicable to this submission, as it describes a mechanical surgical device and not a software-based diagnostic or therapeutic aid.

However, I can extract the relevant information concerning the device's acceptance criteria and performance as described in the document.

1. Table of Acceptance Criteria and Reported Device Performance

The document doesn't explicitly present a table of numerical acceptance criteria with corresponding performance values in the way software performance data might be presented (e.g., "sensitivity > X%" and "achieved Y%"). Instead, it describes general categories of testing and the successful outcomes. The acceptance criteria are implied by the nature of the tests conducted and the statements that the device "meet all pre-established acceptance criteria."

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

The document does not specify exact sample sizes for each test category, nor does it detail data provenance in terms of country of origin or retrospective/prospective studies. It states "Product performance testing for the NovoStitch Pro Meniscal Repair System, size 0 was performed in a simulated use environment." This implies these were bench tests focused on the device's mechanical and functional capabilities.

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

This information is not applicable as the device is a surgical instrument, not a diagnostic device requiring expert interpretation for ground truth. The "ground truth" for this device would be its ability to physically perform its intended function (e.g., deploy a suture correctly, maintain strength).

4. Adjudication Method for the Test Set

This is not applicable for the reasons stated above. Adjudication methods are typically for subjective assessments or disagreements in diagnostic interpretation.

5. If a Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study was done, and Effect Size with AI Assistance

This is not applicable. The device is a surgical tool, not an AI-assisted diagnostic or therapeutic system.

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

This is not applicable. The device is a mechanical surgical instrument, not an algorithm.

7. The Type of Ground Truth Used

The ground truth used for this device's performance evaluation is based on engineering and functional specifications in a simulated use environment (bench testing) and ISO standard requirements for biocompatibility. For instance, whether the suture was reliably deployed, if the device maintained its strength, and whether material components met biocompatibility standards.

8. The Sample Size for the Training Set

This is not applicable. The device is not a machine learning model, and thus does not have a "training set."

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

This is not applicable for the reasons stated above.

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