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Gelsoft™ Plus Vascular Prostheses are indicated exclusively for vascular repair of damaged and diseased vessels of the abdomen, i.e. replacement or bypass in aneurysmal and occlusive disease of abdominal arteries.

Gelsoft™ Plus vascular prostheses are gelatin sealed knitted polyester prosther repair. The Gelsoft™ Plus polyester vascular prosthesis family, which is the subject of this pre-market notification, is based on knitted polyester textile technology.

The provided text describes a 510(k) premarket notification for a medical device called Gelsoft™ Plus Vascular Prostheses. This submission is to demonstrate substantial equivalence to a legally marketed predicate device (K162803 Vascutek Gelsoft™ Plus Vascular Grafts).

The information provided does not include details about acceptance criteria, the specific study conducted, or device performance metrics as would typically be found in a study report. The document states:

"Nonclinical testing, including bench testing, shelf-life, biocompatibility testing, chemical characterization and an animal performance study, have been conducted to demonstrate equivalency. No clinical testing was necessary to demonstrate substantial equivalence."

This indicates that the assessment of substantial equivalence was based entirely on non-clinical data, and therefore, many of the requested categories in your prompt are not applicable to this type of submission.

Here's an analysis based on the information available in the provided text, addressing your points where possible:

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

The document does not provide a table of acceptance criteria or specific reported device performance metrics. Instead, it states that "nonclinical testing... have been conducted to demonstrate equivalency." This implies that the acceptance criteria would be that the new device's performance in these non-clinical tests is equivalent to, or within acceptable predefined limits compared to, the predicate device. However, these specific criteria and results are not detailed.

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

• Sample Size: Not specified for any of the non-clinical tests (bench, shelf-life, biocompatibility, chemical characterization, animal study).
• Data Provenance: Not specified. The applicant is Vascutek Ltd. in the United Kingdom, so the studies likely originated from there or a related testing facility. The studies are non-clinical, not human-patient based, so terms like "retrospective" or "prospective" are not applicable in the usual sense.

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 was a non-clinical assessment, not requiring expert consensus on clinical findings. The "ground truth" would be established by standardized testing methods and measurements.

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

Not applicable. Adjudication methods like "2+1" are used in clinical studies where multiple human readers interpret data. This premarket notification is based on non-clinical tests.

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 device is a vascular prosthesis and not an AI-powered diagnostic or assistive tool.

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

Not applicable. This device is a vascular prosthesis, not a standalone algorithm.

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

The "ground truth" for the non-clinical tests would be based on:

• Established physical and chemical properties measured through bench testing.
• Standardized biocompatibility assessments (e.g., cytotoxicity, irritation).
• Observed effects in an animal model (for the animal performance study).
• Chemical characterization data.

8. The sample size for the training set

Not applicable. This is not an AI/machine learning device that requires a training set.

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

Not applicable.

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