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510(k) Data Aggregation
(120 days)
DentMix VPS Impression Material
DentMix VPS Impression Material is intended for use with all crown and bridge, occlusal and implant impression techniques to reproduce the structure of a patient's teeth and gums.
DentMix VPS Impression Material is an addition-reaction base/catalyst polyviny/siloxane dental impression material intended as an alternative to traditional alginate materials. It is available in regular set and fast set. Both are available in light body, regular body/monophase and heavy body.
The provided document describes the substantial equivalence determination for the "DentMix VPS Impression Material" (K223892) by comparing it to a predicate device, "Elements™" (K151150). The acceptance criteria are based on meeting or exceeding the performance of the predicate device across various physical properties, typically measured against recognized standards like ISO 4823-2015.
Here's the breakdown of the information requested:
Acceptance Criteria and Device Performance
A direct table of "acceptance criteria" is not explicitly stated as distinct from the predicate device's performance. Instead, the study aims to show that the subject device performs at least as well as the predicate device. Therefore, the predicate device's performance serves as the de facto acceptance benchmark.
Acceptance Criteria (Predicate Performance) | Reported Device Performance (DentMix VPS Impression Material) |
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Consistency | |
Heavy Body: 31mm | Heavy Body: 32mm |
Monophase: 35mm | Monophase: 35mm |
Light Body: 39mm | Light Body: 40mm |
Working Time (Regular Set) | |
Heavy Body: 2'30" | Heavy Body: 2'34" |
Monophase: 2'30" | Monophase: 2'12" |
Light Body: 2'30" | Light Body: 2'37" |
Working Time (Fast Set) | |
Heavy Body: 1'30" | Heavy Body: 1'16" |
Monophase: 1'30" | Monophase: 1'23" |
Light Body: 1'30" | Light Body: 1'21" |
Detail Reproduction | PASS |
Linear Dimensional Change | |
Heavy Body: 0.14% (0.01) | Heavy Body: 0.14% (0.01) |
Monophase: 0.05% (0.02) | Monophase: 0.05% (0.02) |
Light Body: 0.08% (0.02) | Light Body: 0.08% (0.02) |
Compatibility with Gypsum | PASS |
Elastic Recovery | |
Heavy Body: 99.7 (0.1) | Heavy Body: 99.1 (0.2) |
Monophase: 99.6 (0.3) | Monophase: 99.1 (0.3) |
Light Body: 99.8 (0.1) | Light Body: 98.9 (0.1) |
Strain-In-Compression | |
Heavy Body: 2.85 (0.1) | Heavy Body: 2.54 (0.8) |
Monophase: 3.67 (0.13) | Monophase: 3.61 (0.4) |
Light Body: 4.93 (0.1) | Light Body: 5.91 (1.6) |
Note on "Acceptance Criteria": For each of these properties, the acceptance criterion implicitly is that the DentMix VPS Impression Material is functionally equivalent to or performs within an acceptable range compared to the predicate device, often guided by the ISO 4823-2015 standard. "PASS" explicitly indicates meeting a standard. For numerical values, the goal is typically to be similar or better.
Study Details for DentMix VPS Impression Material
The document outlines a comparison study to demonstrate substantial equivalence, primarily focusing on physical properties.
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Sample size used for the test set and the data provenance:
- The document does not explicitly state the numerical "sample size" for each test point (e.g., number of specimens tested for consistency, working time, etc.). However, the values reported for "Linear Dimensional Change," "Elastic Recovery," and "Strain-In-Compression" include standard deviations (e.g., "0.14% (0.01)"), which implies that multiple measurements were taken to calculate an average and variability.
- Data Provenance: The document does not specify the country of origin of the data or whether it was retrospective or prospective. It presents the results as part of a 510(k) submission by IPB Inc.
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Number of experts used to establish the ground truth for the test set and the qualifications of those experts:
- This type of detail (number and qualifications of experts) is typically associated with clinical studies or studies where human interpretation or consensus is required (e.g., image analysis). For material property testing as performed here, the "ground truth" is established by direct measurement of physical properties according to standardized test methods (e.g., those described in ISO 4823-2015). Experts in material science or dentistry might design and oversee these tests, but their "consensus" is not the ground truth in the same way it would be for diagnosing a medical image.
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Adjudication method (e.g., 2+1, 3+1, none) for the test set:
- Adjudication methods (e.g., 2+1) are relevant for studies involving human interpretation and potential disagreement (e.g., reading medical images). For physical property testing of dental impression materials, direct measurements are taken, and typically, there is no "adjudication" in this sense. Quality control and adherence to standard protocols ensure reliability.
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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:
- No, an MRMC comparative effectiveness study was not done. This type of study is completely irrelevant for evaluating a dental impression material, as it's a diagnostic tool comparison for medical imaging interpretation, not a material property evaluation.
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If a standalone (i.e. algorithm only without human-in-the-loop performance) was done:
- This question is also not applicable. The device is a physical dental impression material, not an algorithm or AI system. The performance evaluated is the inherent physical properties of the material itself.
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The type of ground truth used (expert consensus, pathology, outcomes data, etc.):
- The "ground truth" for the performance evaluation in this context is the results of standardized physical property tests as defined by recognized standards (specifically ISO 4823-2015). This is a direct measurement of material characteristics against objective criteria, not based on human consensus, pathology, or outcomes data.
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The sample size for the training set:
- This concept is not applicable. The evaluation is a direct comparison of physical material properties against a predicate, not a machine learning model that requires a "training set."
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How the ground truth for the training set was established:
- Not applicable, as there is no training set for this type of device evaluation.
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