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510(k) Data Aggregation
(179 days)
PRESSURE GUARD SITE SELECT (A)
For the prevention and treatment of pressure ulcers.
The PressureGuard Site Select is an air flotation, alternating pressure support system which provides for customized selection of surface firmness for a head, upper torso, lower torso, and heel zones.
The provided 510(k) summary for the PressureGuard Site Select primarily focuses on demonstrating substantial equivalence to a predicate device (PressureGuard IV) based on similar function and intended use. It describes the features and modes of operation of the device but does not include information about specific acceptance criteria or a study proving that the device meets such criteria.
Therefore, I cannot populate most of the requested fields based on the given document.
However, I can extract the following:
1. A table of acceptance criteria and the reported device performance
- Acceptance Criteria: Not explicitly stated in the document.
- Reported Device Performance: Not explicitly stated as per specific performance metrics. The document focuses on describing the device's features and comparability to a predicate.
2. Sample sized used for the test set and the data provenance (e.g. country of origin of the data, retrospective or prospective)
- Sample Size: Not provided.
- Data Provenance: Not provided.
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/Not provided, as there's no mention of a clinical or performance study with a test set requiring ground truth.
4. Adjudication method (e.g. 2+1, 3+1, none) for the test set
- Not applicable/Not provided.
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 not an AI-powered device, and no MRMC study is mentioned.
6. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done
- Not applicable. This is not an algorithm-only device.
7. The type of ground truth used (expert concensus, pathology, outcomes data, etc)
- Not applicable/Not provided.
8. The sample size for the training set
- Not applicable/Not provided, as this is not an AI/machine learning device.
9. How the ground truth for the training set was established
- Not applicable/Not provided.
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