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510(k) Data Aggregation
(154 days)
EPTFE SLFTM SPIRAL VASCULAR GRAFT
The ePTFE SLF™ Spiral Vascular Grafts are indicated for use as vascular prostheses.
The device is intended for use in the bypass or reconstruction of occluded or diseased peripheral arterial blood vessels above or below the knee. Graft configurations are intended for use as arterial conduits for bypass, or reconstruction of peripheral arterial blood vessels.
The device is a vascular graft which has a specially designed section intended to induce spiral laminar flow. The grafts are manufactured from a straight tubular expanded polytetrafluoroethylene (ePTFE) vascular graft, supplied by Vascutek Ltd.
The graft includes a helical overlay of polytetrafluoroethylene (PTFE) beading, injection moulded onto the external surface of the ePTFE tube. The function of the beading is to provide reinforcement for the tube.
This device, the ePTFE SLF™ Spiral Vascular Graft, is a vascular prosthesis. The provided document is a 510(k) summary, which focuses on demonstrating substantial equivalence to predicate devices rather than proving the device meets specific acceptance criteria through a clinical study with a detailed performance table.
Therefore, many of the requested elements regarding acceptance criteria, sample sizes, expert ground truth, adjudication, and comparative effectiveness studies are not applicable in this context.
Here's an analysis based on the provided text:
1. A table of acceptance criteria and the reported device performance
Not Applicable. The 510(k) summary for the ePTFE SLF™ Spiral Vascular Graft does not present specific quantitative acceptance criteria or a direct performance table in the way a clinical trial report would. Instead, it asserts "substantial equivalence" to predicate devices based on technological characteristics and preclinical data.
The performance claim is qualitative:
"Bench testing and animal data demonstrated that the safety and effectiveness of the ePTFE SLF™ Spiral Vascular Grafts is equivalent to the predicate devices."
2. Sample sized used for the test set and the data provenance (e.g. country of origin of the data, retrospective or prospective)
Not specified. The document mentions "bench testing and animal data" but does not provide details on the sample sizes, study design (retrospective/prospective), or data provenance for these tests.
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. Ground truth, in the context of clinical studies and expert review for diagnostic devices, is not relevant here as this is a medical device for implantation, and its safety and effectiveness were established through non-clinical testing.
4. Adjudication method (e.g. 2+1, 3+1, none) for the test set
Not Applicable. See point 3.
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 an implanted medical device, not a diagnostic or AI-assisted interpretation tool. Therefore, MRMC studies and the concept of human readers improving with AI assistance are irrelevant in this context.
6. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done
Not Applicable. See point 5.
7. The type of ground truth used (expert consensus, pathology, outcomes data, etc.)
For the safety and effectiveness determination, the "ground truth" was established through bench testing and animal data. This would typically involve objective measurements of physical properties (e.g., burst strength, flexibility, thrombogenicity) and biological responses in animal models (e.g., patency, tissue integration, absence of adverse reactions), compared against the predicate devices. The document does not detail specific metrics or outcomes data.
8. The sample size for the training set
Not Applicable. There is no "training set" in the context of this 510(k) submission. This is not an AI/ML device that requires a training phase.
9. How the ground truth for the training set was established
Not Applicable. See point 8.
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