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The intended use of the Meniscal Screw is intended for use in the arthroscopic fixation of longitudinal vertical meniscus lesions (bucket handle lesions) located in the vascularized area of the meniscus (red-red and red-white areas).

The Meniscal Screw is a device fabricated from L-PLA which is intended for meniscal repair. The device consists of a cannulated, threaded member designed to be inserted into the meniscus across the tear. The device is screwed into location with the aid of a sterile, single use driver mechanism constructed of stainless steel. The driver is loaded with the Meniscal Screw and placed through a cannula to access the site requiring repair.

The provided text describes a 510(k) submission for the Innovasive Meniscal Screw, which is a medical device. This document is a premarket notification for a traditional medical device, not an AI/ML medical device. Therefore, the information requested about acceptance criteria, device performance, ground truth, and AI/ML specific studies (MRMC, standalone algorithm) is not applicable to this submission.

The document discusses substantial equivalence to a predicate device (Bionx Arrow) based on material, design, and intended use, supported by bench testing and animal testing.

Here's a breakdown of the relevant information from the provided text, structured as much as possible to address your request, acknowledging the non-AI/ML context:

1. Table of Acceptance Criteria and Reported Device Performance

Since this is a submission for a traditional medical device and not an AI/ML algorithm, there are no "acceptance criteria" in the sense of accuracy, sensitivity, or specificity metrics for an algorithm. Instead, the "acceptance criteria" can be inferred as the performance deemed equivalent to the predicate device to ensure safety and effectiveness.

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

This information is not provided in the 510(k) summary.

• Test Set Sample Size: Not specified for bench or animal testing.
• Data Provenance: Not specified (e.g., country of origin, retrospective/prospective).

3. Number of Experts Used to Establish Ground Truth and Qualifications

This concept is not applicable here as there is no "ground truth" in the context of expert labeling for an AI algorithm. The studies involve device performance (mechanical and biological), not interpretation of data by experts.

4. Adjudication Method for the Test Set

Not applicable. This is not a study requiring adjudication of interpretations.

5. If a Multi Reader Multi Case (MRMC) Comparative Effectiveness Study was done

No, an MRMC comparative effectiveness study was not done. This type of study is relevant for AI/ML algorithms that assist human readers.

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

No, a standalone algorithm performance study was not done. This is not an AI/ML device.

7. The Type of Ground Truth Used

The "ground truth" in this context refers to the validated measurements and observations from the bench and animal studies to determine the physical and biological performance of the device.

• Bench Testing: Mechanical properties (fatigue strength, constant load performance, weight loss, intrinsic viscosity) measured against established scientific standards and comparison to the predicate device.
• Animal Testing: In vivo observations of efficacy and proper functioning to meet intended use, likely through histological analysis, gross observations, and potentially biomechanical assessments in an animal model.

8. The Sample Size for the Training Set

Not applicable. There is no training set as this is not an AI/ML device.

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

Not applicable. There is no training set.

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