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Biodesign Anal Fistula Plug: For implantation to reinforce soft tissue where a rolled configuration is required, for repair of anal, rectal and enterocutaneous fistulas.
Biodesign Fistula Plug: For implantation to reinforce soft tissue for repair of recto-vaginal or anorectal fistulas.
Biodesign Plastic Surgery Matrix: For implantation to reinforce soft tissue where weakness exists in patients requiring soft tissue repair or reinforcement in plastic or reconstructive surgery.
Biodesign Tissue Graft: For implantation to reinforce soft tissue.

All four subject devices of this bundled submission are part of a family of devices manufactured by Cook Biotech Incorporated (CBI) consisting of processed porcine small intestinal submucosa (SIS), a three-dimensional, acellular, collagen-based extracellular matrix (ECM) material. SIS is manufactured by first removing the tunica mucosa from the inner intestinal surface and the serosa and tunica muscularis from the outer surface of the porcine small intestine. Further processing removes the cells and renders the material virally inactive. leaving behind a three- dimensional, decellularized, collagen-rich extracellular matrix.

This document does not contain an acceptance criteria table or a study proving the device meets specific performance criteria. Instead, it is a 510(k) premarket notification of intent to market for several Biodesign devices. The submission aims to demonstrate substantial equivalence to already marketed predicate devices, not to prove performance against specific acceptance criteria.

The core of the submission, as per the snippets provided, is that the subject devices are largely identical to their predicate devices, with the only change being the inclusion of additional rehydration fluid options in the instructions for use (IFUs).

Here's a breakdown of the requested information based on the provided text, highlighting what is present and what is absent:

1. A table of acceptance criteria and the reported device performance:
* Absent. This document does not present specific acceptance criteria with corresponding performance data. The submission focuses on demonstrating substantial equivalence to predicate devices, which implies that the device's performance is expected to be similar or equal to that of the predicates. The closest information is a comparison of characteristics between the subject devices and predicate devices (Table 5-3 on page 8).

2. Sample size used for the test set and the data provenance (e.g., country of origin of the data, retrospective or prospective):
* Absent. The document mentions "Mechanical testing (burst strength, tensile strength, suture retention strength and delamination testing) performed on devices rehydrated with new rehydration fluid options" to demonstrate no negative effects on mechanical properties. However, it does not specify the sample size used for these tests, the data provenance, or whether the study was retrospective or prospective.

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 / Absent. This type of information is typically relevant for studies involving human interpretation (e.g., diagnostic imaging). This submission describes mechanical testing of a medical device (surgical mesh), not expert-based assessment.

4. Adjudication method (e.g., 2+1, 3+1, none) for the test set:
* Not applicable / Absent. Similar to point 3, adjudication methods are usually for expert consensus on results, which is not described here for mechanical testing.

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 pertains to a surgical mesh, not an AI-assisted diagnostic device. Therefore, no MRMC study or AI-related effectiveness analysis is presented.

6. If a standalone (i.e., algorithm only without human-in-the-loop performance) was done:
* Not applicable. This is not an algorithm or AI device.

7. The type of ground truth used (expert consensus, pathology, outcomes data, etc.):
* The "ground truth" for the mechanical testing would be the measured mechanical properties (burst strength, tensile strength, suture retention strength, delamination) of the device. The aim was to show that these properties, when rehydrated with new fluid options, were comparable to those rehydrated with saline. The text states: "...demonstrate the devices still performed as expected and there were no negative effectives on the mechanical properties."

8. The sample size for the training set:
* Not applicable. There is no "training set" as this is not an AI/machine learning device.

9. How the ground truth for the training set was established:
* Not applicable. As there is no training set, this information is not relevant.

In summary, the provided document is a 510(k) summary focused on demonstrating substantial equivalence for modifications to existing surgical mesh devices, primarily concerning rehydration fluid options. It describes mechanical testing performed to ensure the modified devices retain expected properties but does not detail acceptance criteria or study specifics in the format requested, which is typical for performance studies of AI/diagnostic devices.

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The Biodesign® Diaphragmatic Hernia Graft is intended for implantation to reinforce soft tissues where weakness exists including the repair of diaphragmatic/hiatal hernias.

The graft is supplied sterile and is intended for one time use only.

The Biodesign® Diaphragmatic Hernia Graft, the subject device, has the same indications for use and is physically identical to the predicate device (K133011) with the same name. The only difference between the subject device and the predicate device is the rehydration fluid options described in the devices' instructions for use (IFU).

Both the subject and predicate devices are part of a family of implant devices manufactured from porcine small intestine that have been processed to remove the tunica mucosa from the inner intestinal surface and the serosa and tunica muscularis from the outer intestinal surface. After further disinfection to ensure the material is virally inactive, the resulting layer is a three dimensional, acellular, collagen-rich extracellular matrix (ECM) that is termed small intestinal submucosa (SIS). Both the subject and predicate devices are multilayered SIS sheets configured in two shapes: rectangular shape (7 x 10 cm) and the U-cut shape (7 x 10 cm with U-shaped notch). Both devices are perforated and have polyglycolic acid (PGA) suture stitched across the device and around the perimeter. The purpose of the suture stitching is to prevent delamination due to device handling during implantation. Both devices are provided in a double Tyvek® pouch and are ethylene oxide (EO) sterilized.

Prior to implantation, the Biodesign® Diaphragmatic Hernia Graft, the subject device, can be rehydrated with sterile saline or autologous body fluids (e.g., blood, bone marrow aspirate, or blood concentrates such as platelet concentrate).

Upon implantation, the Biodesign® Diaphragmatic Hernia Graft (both subject and predicate device) will provide mechanical reinforcement of soft tissue in the repair of diaphragmatic/hiatal hernias. Over time, the device will incorporate (remodel) into the body such that no graft material is left behind.

The provided document is a 510(k) summary for a medical device called the Biodesign® Diaphragmatic Hernia Graft. It describes the device, its intended use, and why it is considered substantially equivalent to a predicate device.

However, the document does not contain information about a study that proves the device meets specific acceptance criteria in the context of an AI/ML medical device, which is what your detailed questions are tailored to. The device in focus (a surgical mesh) is a physical implant, not a software or AI-driven diagnostic or therapeutic tool.

Therefore, I cannot answer questions 1 through 9 directly from the provided text, as they pertain to the evaluation of an AI/ML system's performance and validation.

The document's "Performance Data" section discusses non-clinical testing (mechanical properties, tensile strength, suture retention strength, hydration time, and simulated use/handling properties) to show that a new rehydration fluid option does not significantly change the device's properties compared to the predicate device. This is a very different type of "performance data" than what would be generated for an AI/ML medical device.

In summary, the provided text does not contain the information required to answer your specific questions.

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