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Bard Composix L/P Mesh is indicated for use in the reconstruction of soft tissue deficiencies, such as for the repair of hernias and chest wall defects.

The Composix® L/P Mesh, will consist of a layer of polypropylene mesh and a layer of expanded polytetrafloroethylene (ePTFE) stitched together using Polytetrafluroethylene (PTFE) monofilament thread sewn in a lock stitch formation. The polypropylene layer is knitted from 0.0048 inch polypropylene monofilament, which is identical to the currently marketed Large Pore Soft™ Mesh. The thickness of the ePTFE layer is identical to the currently marketed Composix® E/X Mesh. As with the currently marketed Composix E/X, the peripheral edge of the polypropylene mesh will be heat sealed to the ePTFE layer.

The layers of the Composix L/P Mesh will be sewn together using rows of interspaced stitching, which will allow the surgeon to tailor the product. Using the stitch pattern as a guide, the surgeon can tailor the product. For user convenience to facilitate the deployment of the larger sized Composix L/P products, the larger sizes of the Composix L/P products will be packaged with an Introducer Tool. This Introducer Tool is similar to the rolling tines/plunger assembly and T-handle of the PrecisionPass™ Delivery Device. The Introducer Tool consists of a handle with a thin stainless steel rod. The stainless steel rod is split into two pieces along its length and has ridges around the perimeter to facilitate use. Similar to the T-handle provided with the PrecisionPass Device, the Introducer Tool's T-cap will be used to secure the open end of the metal rolling tines during the rolling process, then removed prior to delivering the device through the trocar.

This document is a 510(k) Summary for the Bard Composix® L/P Mesh, a surgical mesh. The submission focuses on demonstrating substantial equivalence to predicate devices, rather than establishing de novo acceptance criteria through a clinical study with detailed performance metrics. Therefore, many of the requested elements for a typical AI/software device study are not directly applicable or available in this type of submission.

Here's an analysis of the provided text in relation to your questions:

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

This
submission does not define specific quantitative "acceptance criteria" in the way an AI/software device would, nor does it report numerical "device performance" in terms of accuracy, sensitivity, or specificity. The acceptance criteria in a 510(k) for a medical device like a surgical mesh are typically based on demonstrating substantial equivalence in materials, design, manufacturing, intended use, and performance characteristics to a legally marketed predicate device.

The "performance" reported primarily revolves around demonstrating that the new device is as safe and effective as the predicate devices.

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

The submission does not describe a "test set" in the context of evaluating an AI/software device. The performance data is based on "Biocompatibility and bench testing." These types of tests involve material samples and controlled laboratory experiments, not patient data in the typical sense of a "test set" for diagnostic performance. Therefore, sample sizes for patient data, country of origin, and retrospective/prospective nature are not applicable here.

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)

Not applicable. This is a physical surgical mesh, not an AI/software device that requires expert-established ground truth on patient data.

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

Not applicable. This is a physical surgical mesh, not an AI/software device that requires expert 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 is a physical surgical mesh, not an AI or diagnostic device that would involve human readers or MRMC studies.

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

Not applicable. This is a physical surgical mesh, not an algorithm.

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

The ground truth for a physical device like a surgical mesh is established through a combination of:

• Material specifications and standards: Confirming the physical and chemical properties of the materials meet established safety and performance benchmarks.
• Biocompatibility testing: Demonstrating the material does not cause adverse biological reactions.
• Bench testing: Laboratory tests to evaluate mechanical properties (e.g., tensile strength, tear resistance) and other functional aspects relevant to its use as a surgical mesh.
• Predicate device history: Relying on the established safety and effectiveness profile of the legally marketed predicate devices, combined with evidence that the new device is sufficiently similar.

The document states: "Biocompatibility and bench testing provided in this submission support the safety and effectiveness of Bard Composix® L/P Mesh for its intended use." and "Laboratory testing discussed in this submission demonstrate that the material chosen and the design utilized in manufacturing Bard Composix® L/P Mesh is substantially equivalent to the referenced Predicate Products."

8. The sample size for the training set

Not applicable. This is a physical surgical mesh, not an AI/software device that requires a training set.

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

Not applicable. This is a physical surgical mesh, not an AI/software device that requires a training set with ground truth.

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