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Inguinal hernia repair via anterior tension-free approach.

The proposed ProGrip™ self-gripping polypropylene mesh is available in 2 forms;

• Pre-cut, elliptic mesh with slit and self-gripping, overlapping flap. Right or left anatomical side.
• Rectangular mesh.
  The mesh and the overlapping flaps of the pre-cut versions are made of knitted monofilament polypropylene with polylactic acid monofilament resorbable hooks on one of the sides. These hooks facilitate placing, positioning and temporary fixation of the overlapping flap and the mesh to the surrounding tissue. A colored yarn marker is placed on the medial edge of the pre-cut mesh to help with orientation.
  The subject modified ProGrip™ self-gripping polypropylene mesh is different from the predicate ProGrip™ self-gripping polypropylene mesh (K140941) in labeling and new sterilizer facilities with the same ethylene oxide method. There is no change to the technology, engineering, or material specifications.

This document is a 510(k) premarket notification for a medical device called "ProGrip Self-Gripping Polypropylene Mesh." The purpose of this submission is to demonstrate that the revised device is substantially equivalent to a legally marketed predicate device (K140941). The primary changes described are related to labeling updates and the addition of new sterilization facilities using the same ethylene oxide (EO) method.

Given this context, the request to describe "acceptance criteria and the study that proves the device meets the acceptance criteria" in terms of AI/algorithm performance (e.g., impact on human readers, standalone performance, ground truth establishment, training set details) is not applicable to this specific submission.

Here's why, and what information can be extracted relevant to the submission:

Key Takeaway: This is a 510(k) for a physical medical device (surgical mesh), not an AI/Software as a Medical Device (SaMD). The "studies" conducted are non-clinical validations related to manufacturing processes, not diagnostic algorithm performance.

Therefore, I cannot provide the requested information for AI/algorithm performance. However, I can explain the acceptance criteria and supporting "studies" (validations) for this physical device:

Acceptance Criteria and Supporting Studies for ProGrip Self-Gripping Polypropylene Mesh (K220540)

This 510(k) submission primarily focuses on demonstrating that the changes made to the ProGrip Self-Gripping Polypropylene Mesh (labeling and new sterilization facilities) do not alter its substantial equivalence to the predicate device (K140941) regarding safety and effectiveness. The "acceptance criteria" here relate to maintaining established standards for sterilization, aeration, biocompatibility, and product performance.

1. Table of Acceptance Criteria and Reported Device Performance

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

• Sample Size: Not explicitly stated as "sample size" in the context of a test set for diagnostic performance. Instead, validation studies were performed on product batches from the new sterilization sites. The specific number of units tested for sterilization, EtO residuals, and stability would be detailed in the underlying validation reports, but this summary document does not provide those specific numbers.
• Data Provenance: The data comes from internal validation studies conducted by Covidien/Medtronic, related to their manufacturing processes and new sterilization facilities. The location of these new facilities is not specified (e.g., country), but the general context is a US FDA submission. The studies are by nature prospective validations of the manufacturing and sterilization processes.

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

• Not Applicable. This is not an AI/diagnostic device. "Ground truth" in this context would relate to established standards (e.g., ISO for sterilization, biocompatibility, EtO residuals) and the qualifications of the engineers/scientists conducting the validation tests, not expert readers.

4. Adjudication method for the test set

• Not Applicable. This is not an AI/diagnostic device where adjudication of diagnostic outputs by multiple experts is relevant. Compliance with standards is demonstrated through test results.

5. If a Multi-Reader Multi-Case (MRMC) comparative effectiveness study was done

• Not Applicable. This is not an AI/diagnostic device, so MRMC studies comparing human reader performance are irrelevant.

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

• Regulatory/Engineering Standards: The "ground truth" for this submission is adherence to established regulatory and engineering standards (e.g., ISO 10993-1 for biocompatibility, ISO 10993-7 for EtO residuals), and internal quality system validation protocols for sterilization and product performance. The predicate device (K140941) also serves as a benchmark for equivalence.

8. The sample size for the training set

• Not Applicable. This is a physical surgical mesh, not an AI/machine learning model, so there is no "training set."

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

• Not Applicable. See #8.

In summary, the provided document is a regulatory submission for a physical medical device. The "acceptance criteria" and "studies" it references are related to demonstrating the continued safety and effectiveness of the device despite manufacturing and labeling changes, primarily through non-clinical validation testing against established industry and regulatory standards.

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PROGRIP™ Self-Gripping Polypropylene Mesh is intended for the reinforcement of tissue during surgical repair.
Parietene™ Flat Sheet Mesh is intended for the reinforcement of tissue during surgical repair.
PROGRIP™ Self-Gripping Polypropylene Mesh is indicated for inguinal and incisional hernia repair.
Parietene™ Flat Sheet Mesh is indicated for inguinal hernias, parietal reinforcement of tissues and abdominal wall hernia repair.

PROGRIP™ Self-Gripping Polypropylene Mesh: The mesh and the overlapping flaps of the pre-cut versions are made of knitted monofilament polypropylene with polylactic acid monofilament resorbable hooks on one of the sides. These hooks facilitate placing, positioning and temporary fixation of the overlapping flap and the mesh to the surrounding tissue. A colored yarn marker is placed on the medial edge of the pre-cut mesh to help with orientation.
Parietene™ Flat Sheet Mesh: Parietene™ Flat Sheet Mesh is a Monofilament polypropylene mesh.

The provided text describes a 510(k) submission for two surgical mesh devices, PROGRIP™ Self-Gripping Polypropylene Mesh and Parietene™ Flat Sheet Mesh. The submission seeks to add a new formulation of raw material (polypropylene) from the same yarn supplier.

Here's an analysis of the acceptance criteria and study information:

1. Table of Acceptance Criteria and Reported Device Performance

The document states, "The results of the bench and preclinical tests demonstrate that proposed devices are substantially equivalent to the predicates Parietene™ PROGRIP Mesh (K101197) and Parietene™ Polypropylene Mesh (K991400)." This implies that the device met the acceptance criteria by demonstrating substantial equivalence through various tests.

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

The document does not explicitly state the sample size used for the test set of the performance studies. It mentions "bench testing" and "preclinical tests." The provenance of the data (e.g., country of origin, retrospective or prospective) is also not specified.

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

This information is not provided in the document. The studies mentioned are bench and preclinical tests, which typically do not involve expert interpretation for ground truth in the same way clinical image analysis studies would.

4. Adjudication Method for the Test Set

This information is not provided as the studies are bench and preclinical tests, not clinical studies requiring adjudication of output.

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 such study was conducted or mentioned. This submission is for a surgical mesh, not an AI-powered diagnostic or assistive device.

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 (surgical mesh), not an algorithm or AI system. The performance studies are focused on the material properties and biocompatibility of the mesh.

7. The Type of Ground Truth Used

For the bench testing, the ground truth would likely be established through standard engineering and materials science measurements, comparing the new material's performance to established specifications or the predicate devices' performance.

For biocompatibility, the ground truth would be established through standard cytotoxicity, sensitization, irritation, etc., testing as per ISO 10993-1, determining if the material elicits an unacceptable biological response.

8. The Sample Size for the Training Set

Not applicable. This is a physical medical device, not a machine learning model, so there is no concept of a "training set" in this context.

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

Not applicable, as there is no training set for a physical surgical mesh device.

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