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510(k) Data Aggregation
(225 days)
The ULTRAPRO COMFORT PLUG Partially Absorbable Hernia Repair Device is indicated for reinforcement of soft tissue, where weakness exists, in procedures involving soft tissue repair, such as groin hernia defects.
ULTRAPRO COMFORT PLUG is a sterile, single-use partially absorbable hernia repair device designed for open extra-peritoneal abdominal wall repair, particularly groin hernia repair, to provide permanent support during and following wound healing. ULTRAPRO COMFORT PLUG consists of a three-dimensional plug, which fills the defect and a flat pre-shaped onlay patch, which lays on the defect to reinforce the weak area around the defect. The Plug is composed of an undyed ULTRAPRO Mesh. Dyed ribs, made from dyed (D&C Violet No. 2) polydioxanone polymer film, are laminated to the Plug mesh. The onlay patch is a pre-shaped, dyed ULTRAPRO Mesh. The ULTRAPRO Mesh is manufactured from approximately equal parts of absorbable poliglecaprone 25 monofilament fibers and non-absorbable polypropylene monofilament fibers. The device is available in different sizes.
This document describes a 510(k) submission for the ULTRAPRO COMFORT PLUG™ Partially Absorbable Hernia Repair Device. This is a medical device and not an AI/ML-based diagnostic system, thus many of the requested criteria (like sample size for test/training, number of experts, MRMC studies, ground truth establishment, etc.) are not applicable to this type of regulatory submission. The performance assessment for this device focuses on biocompatibility, physical dimensions, shelf life, and animal model efficacy, rather than diagnostic accuracy metrics common in AI/ML studies.
Here's a breakdown of the available information based on your request, highlighting what is not applicable:
1. A table of acceptance criteria and the reported device performance
The document does not present a formal table of quantitative acceptance criteria for device performance with specific metrics like sensitivity, specificity, or AUC, as would be common for diagnostic AI/ML devices. Instead, the device's performance is demonstrated through a comprehensive testing program that confirms safety and effectiveness in line with its intended use and provides substantial equivalence to predicate devices.
Acceptance Criterion (Implicit) | Reported Device Performance |
---|---|
Biocompatibility (per ISO 10993-1:2009) | Passed tests for cytotoxicity, sensitization, acute systemic toxicity, pyrogenicity, subchronic toxicity, genotoxicity, and local tissue response and absorption study. |
Device Dimensional Measurement | Bench testing conducted for device dimensional measurement and comparison, indicating conformance. Specific measurements or criteria are not detailed in this summary. |
Shelf Life | Shelf life testing was conducted. Specific duration or stability metrics are not detailed in this summary. |
Performance/Efficacy in Animal Model (Hernia Repair) | Efficacy study evaluating mesh compression, tissue integration, and tissue reaction was conducted in an animal model. Infection potentiation study was also done. Results demonstrate the device "performs as intended." Specific quantitative outcomes are not detailed. |
Substantial Equivalence to Predicate Devices (ULTRAPRO PLUG™, BARD Mesh Perfix™ Plug) | Performance data (bench and animal testing) supports that the device is "as safe and as effective" as the predicate devices for the intended use, and shares "same intended use, fundamental scientific technology, and principles of operation." |
2. Sample size used for the test set and the data provenance
- Sample Size for Test Set: Not explicitly stated in terms of patient numbers or a "test set" in the context of diagnostic data. The document mentions "bench and animal testing." For animal studies, specific numbers of animals are not provided in this summary.
- Data Provenance: The studies were conducted by the manufacturer, Johnson & Johnson MEDICAL GmbH, in Germany. The nature of the studies (biocompatibility, bench, animal models) means the data is prospective for the purpose of demonstrating device safety and performance. No patient data provenance (e.g., country of origin, retrospective/prospective) is relevant here as it's a hardware medical device submission.
3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts
- Not Applicable. This is a hardware medical device, not an AI/ML diagnostic. There is no "ground truth" established by human experts in the way that would apply to image interpretation or diagnostic accuracy studies. The "ground truth" for this device's performance is based on established biological and engineering principles, and validated test methods (e.g., ISO standards for biocompatibility).
4. Adjudication method (e.g. 2+1, 3+1, none) for the test set
- Not Applicable. No adjudication method is relevant as this is not a diagnostic accuracy study involving human readers.
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 medical device (surgical mesh), not an AI-assisted diagnostic tool.
6. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done
- Not Applicable. This is a physical medical device. There is no "algorithm only" performance.
7. The type of ground truth used (expert consensus, pathology, outcomes data, etc.)
- The "ground truth" for this device's acceptance is based on:
- Validated Test Standards: ISO 10993-1:2009 for biocompatibility.
- Engineering Specifications: For device dimensions and physical properties.
- Biological Response in Animal Models: Evidence of "efficacy study evaluating mesh compression, tissue integration, and tissue reaction and infection potentiation study."
- Comparison to Predicate Devices: Demonstrating equivalence in materials, function, and performance to legally marketed predicate devices.
8. The sample size for the training set
- Not Applicable. This device is not an AI/ML model that requires a training set.
9. How the ground truth for the training set was established
- Not Applicable. As above, no training set or associated ground truth.
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