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TO SEAL THE SURFACE OF: DIRECT COMPOSITE RESTORATIONS INDIRECT COMPOSITE RESTORATIONS AMALGAM RESTORATIONS INTRACORONAL SPLINTS EXTRACORONAL SPLINTS LINGUAL RETAINERS ENAMEL SURFACES AROUND ORTHODONTIC BRACKETS PROVISIONAL RESTORATIONS PROCESSED ACRYLIC PROSTHESES-REMOVABLE PARTIAL & COMPLETE DENTURES AND MAXILLOFACIAL PROSTHESES PROCESSED ACRYLIC APPLIANCES-ORTHODONTIC RETAINERS

BISCOVER LIQUID POLISH contains Hexafunctional Urethane Acrylate (30%), Polyethylene Glycol Diacrylate (26%), Ethoxylated Bisphenol A Diacrylate (34%), Trifunctional Acid Ester (3%), TPO (7%), MEHQ (Inhibitor) 500 ppm. It is supplied in a bottle. It is applied with a brush to seal the surface of a composite restoration. BISCOVER VISCOSITY MODIFIER is acetone and is used to reduce the thickness of the BISCOVER LIQUID POLISH.

The provided document, K030354 for BISCOVER LIQUID POLISH KIT, does not contain a description of acceptance criteria or a study proving that the device meets those criteria in the way typically required for AI/ML-based medical devices.

The document is a 510(k) premarket notification for a dental surface sealant. The approval is based on substantial equivalence to a predicate device (Fortify K882915). The "Significant Performance Characteristics" section compares the applicant device (BISCOVER LIQUID POLISH) to the predicate based on intended use, product description (clear solution), and delivery system (brush). These are qualitative comparisons related to the basic function and form of the product, not quantitative performance metrics that would typically have acceptance criteria.

Therefore, I cannot provide the requested information for acceptance criteria and a study that proves the device meets them because such information is not present in the provided text.

Here is a breakdown of why each requested point cannot be answered:

1. A table of acceptance criteria and the reported device performance: No specific, quantitative acceptance criteria are stated. The "Significant Performance Characteristics" table only lists descriptive characteristics for substantial equivalence.
2. Sample size used for the test set and the data provenance: Not applicable. There is no performance study described with a test set.
3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts: Not applicable. No ground truth establishment process is described.
4. Adjudication method for the test set: Not applicable. No test set or adjudication process is described.
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/ML device.
6. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done: Not applicable. This is not an AI/ML device.
7. The type of ground truth used: Not applicable. The "proof" of safety and efficacy relies on biocompatibility testing and substantial equivalence to a predicate, not performance against a specific ground truth.
8. The sample size for the training set: Not applicable. There is no "training set" for this type of device.
9. How the ground truth for the training set was established: Not applicable. No training set or ground truth establishment is described.

The submission focuses on chemical composition, biocompatibility (stated as "nontoxic" without details of the tests), and functional similarity to an existing legally marketed device to claim substantial equivalence. It does not involve performance studies as one would expect for an AI/ML diagnostic or therapeutic device.

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