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ProGrip™ laparoscopic self-fixating mesh is indicated for the reinforcement of soft tissues during repair of inguinal hernia defects by laparoscopic approach.

Both the predicate and the proposed mesh are made of knitted monofilament polyester with monofilament polylactic acid resorbable grips on one side and a resorbable film made of collagen from porcine origin and glycerol, on the other side. The grips allow positioning and fixation of the mesh to the surrounding tissue, while the collagen film facilitates mesh handling and deployment. The mesh incorporates a green band to facilitate orientation.

The monofilament polylactic acid grips are bioresorbable and provide the fixation of the mesh to surrounding tissue for at least 8 weeks. The polylactic acid grips degrade and resorb in vivo by hydrolysis and are metabolized by the body into CO2 and H2O.

The provided text describes a 510(k) submission for Sofradim Production's ProGrip™ Laparoscopic Self-Fixating Mesh, seeking to add new sizes to an existing product family. The document focuses on demonstrating substantial equivalence to a predicate device, rather than presenting a standalone study with detailed acceptance criteria and performance metrics for a medical device that produces quantitative or qualitative outputs (like an AI/ML algorithm).

Therefore, based on the provided text, it's not possible to provide a table of acceptance criteria and reported device performance in the way typically expected for an AI/ML device or a device with measurable performance output. The "performance data" mentioned in the document refers to physical characteristics and compatibility of the mesh sizes with trocars, not clinical outcomes or diagnostic accuracy.

Here's an analysis based on the information provided, recognizing the limitations:

1. Table of Acceptance Criteria and Reported Device Performance

As this submission is for a physical medical device (surgical mesh) and primarily concerns adding new sizes, the "acceptance criteria" are related to physical properties and compatibility, not a performance metric like sensitivity, specificity, or accuracy for an AI/ML device.

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

• Sample Size: Not explicitly stated. The text mentions "bench performance evaluations were completed to verify that the proposed additional sizes... are compatible with 10mm and/or 12mm trocars." It doesn't specify how many meshes of each size were tested.
• Data Provenance: This is bench testing of physical devices (surgical mesh). The country of origin of the data is not specified, but the submitter is "Sofradim Production (subsidiary of Covidien LLC)" with an address in Trevoux, France. The data is prospective in the sense that it was generated for this submission.

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

Not applicable. The "ground truth" for this type of physical device testing is the direct measurement and observation of physical properties and functionality (e.g., whether the mesh passes through the trocar, visual integrity, number of gripping points). It does not involve expert interpretation or diagnosis.

4. Adjudication Method for the Test Set

Not applicable. This is objective bench testing of physical properties, not a subjective assessment requiring adjudication.

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

Not applicable. This submission is for a physical surgical mesh, not an AI/ML diagnostic or assistive device.

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

Not applicable. This is for a physical surgical mesh.

7. The Type of Ground Truth Used

The ground truth for the bench testing was based on:

• Direct observation of physical events (passage through trocar).
• Visual inspection criteria.
• Quantitative measurement against a defined specification (e.g., number of gripping points).

8. The Sample Size for the Training Set

Not applicable. This is not an AI/ML device; therefore, there is no training set in that context. The "training" in manufacturing comes from established material compositions and manufacturing processes which are stated to be unchanged from the predicate device.

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

Not applicable. As there is no AI/ML training set, this question is not relevant. The "ground truth" for the predicate device's design and manufacturing processes would have been established through extensive design validation, material testing, and historical performance data, none of which are detailed here beyond the statement of "ProGrip™ Laparoscopic Self-Fixating Mesh new sizes are composed of biocompatible materials that are in compliance with ISO 10993-1 standard." and that materials and manufacturing processes have not changed.

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