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510(k) Data Aggregation
(80 days)
The Vertex Rapid Simplified is indicated for: 1. Fabrication of full dentures 2. Fabrication of partial dentures
The Vertex hot-curing denture base material is a conventional dough pack heat cured denture base material that consists of polymethyl methacrylate powder with a heat cure monomer consisting of methyl methacrylate. This material complies with the requirements of ISO 1567, Dentistry. Denture base polymers. The pressing technique is the processing method for Vertex hot-curing denture base material. This cadmium-free acrylic has a rapid 20 minutes polymerization cycle (overnight polymerization is also possible). The Vertex hot-curing denture base powder is available in 10 shades.
Here's an analysis of the provided text regarding the Vertex Dental B.V. Vertex hot-curing denture base material, focusing on acceptance criteria and study details.
1. Table of Acceptance Criteria and Reported Device Performance
| Feature | Acceptance Criteria (from predicate devices / ISO standards) | Vertex Rapid Simplified Performance |
|---|---|---|
| Charpy impact strength | ≥ 1.36 kj/m² (from predicate devices) | 11.3 kj/m² |
| Flexural strength | ≥ 78 MPa (from predicate devices) | 85 MPa |
| Flexural modulus | ≥ 2367 MPa (from predicate devices) | 2367 MPa |
| Water absorption | ≤ 22.0 µg/mm³ (from predicate devices) | 22.5 µg/mm³ |
| Water solubility | ≤ 1.5 µg/mm³ (from predicate devices) | 0.11 µg/mm³ |
| Residual monomer | < 2.2% (from predicate devices) | 1.33 ± 0.16% |
Note: The acceptance criteria are inferred from the performance data of the predicate devices (Probase Hot and Major.Base 20) against which the Vertex Rapid Simplified is compared for substantial equivalence, and by referring to the ISO 1567 standard. The document states that the material complies with ISO 1567, implying these values meet or exceed the standard's requirements.
2. Sample size used for the test set and the data provenance
The provided 510(k) summary does not explicitly state the sample sizes used for the material property tests. It provides mean values and, in some cases, standard deviations, but not the 'n' value for the number of samples tested for each property.
The data provenance is not specified in terms of country of origin or whether it's retrospective or prospective. It is implied to be laboratory testing conducted by the manufacturer to demonstrate compliance with standards and equivalence to predicate devices.
3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts
This information is not applicable as the described study is a series of material property tests, not a clinical study involving expert interpretation or ground truth establishment in a medical context.
4. Adjudication method for the test set
This information is not applicable as the described study is a series of material property tests, not a clinical study requiring adjudication of expert opinions.
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
This information is not applicable. This submission concerns a dental material's physical and chemical properties, not a medical imaging or AI-assisted diagnostic device.
6. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done
This information is not applicable. This submission concerns a dental material, not an algorithm or AI device.
7. The type of ground truth used (expert consensus, pathology, outcomes data, etc.)
The "ground truth" in this context refers to the established physical and chemical property testing standards (e.g., ISO 1567, ISO 179-1, ISO 20795, ISO 7405, ASTM F 895-84). The device's performance is measured against these objective standards and compared to legally marketed predicate devices, which are also compliant with these standards.
8. The sample size for the training set
This information is not applicable. This is not a machine learning or AI-based device, so there is no concept of a "training set."
9. How the ground truth for the training set was established
This information is not applicable. As stated above, this is not a machine learning or AI-based device.
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