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510(k) Data Aggregation
(45 days)
Poly Q Garant L: Wash material for dual phase impression techniques. Poly Q Penta M: Impression material for monophase technique. Poly Q Penta H: Tray material for dual phase impression techniques.
Poly Q is classified as Impression material ( 21 C.F.R. § 872.3660) because it is a device intended to reproduce the structure of a patient's teeth. Poly Q will be available in three different viscosities, called Poly Q Garant™ L (light body), Poly Q Penta™ M (medium body) and Poly Q Penta™ H (heavy body). Poly Q Penta M and Poly Q Penta H are two component (base paste/catalyst) materials to automatically be mixed in dispensed in 3M ESPE's Pentamix™ device. Poly Q Garant L is a material designed to be used in 3M ESPE's mixing, dosing and dispensing device, Garant™.
The provided text describes the 510(k) premarket notification for the Poly Q impression materials (Poly Q Garant L, Poly Q Penta M, Poly Q Penta H). The submission mostly focuses on demonstrating substantial equivalence to predicate devices rather than presenting a detailed study with specific acceptance criteria and performance metrics in the format requested.
Therefore, many of the requested data points are not explicitly available in the provided text. However, based on the information provided, here's what can be extracted:
1. Table of Acceptance Criteria and Reported Device Performance:
The document broadly states that "To prove the effectiveness of Poly Q, the performance characteristics of Poly Q Garant L, Poly Q Penta M and Poly Q Penta H were compared to the respective predicate devices." However, it does not specify what those performance characteristics were, how they were measured, or what the acceptance criteria for those characteristics were. It only concludes that "the impression materials...are, in our opinion, substantially equivalent to the respective predicate devices." This implies that the performance was deemed acceptable if it was similar enough to the predicate devices.
| Acceptance Criteria | Reported Device Performance |
|---|---|
| Not explicitly stated. Implied: Performance characteristics must be substantially equivalent to predicate devices (Impregum™ Garant™ L DuoSoft, Impregum™ Penta™ M Monosoft, Impregum™ Penta™ H DuoSoft). | Poly Q Garant L, Poly Q Penta M, and Poly Q Penta H were found to be substantially equivalent to their respective predicate devices. Specific performance metrics and quantifiable comparisons are not provided. |
2. Sample Size Used for the Test Set and Data Provenance:
Not explicitly stated. The document mentions "biocompatibility testing" and "performance characteristics comparison," but does not provide details on the sample sizes used for these tests or the data provenance (e.g., country of origin, retrospective/prospective).
3. Number of Experts Used to Establish the Ground Truth for the Test Set and Qualifications of Those Experts:
Not explicitly stated. The document does not describe a process of establishing ground truth with experts in the context of device performance testing.
4. Adjudication Method for the Test Set:
Not explicitly stated. Given the nature of a substantial equivalence submission for impression materials, it's unlikely that an adjudication method for a test set (as would be applicable for imaging or diagnostic algorithms) was employed or described in this type of document.
5. Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study:
No. This type of study is not mentioned or implied as it's typically used for AI-assisted diagnostic tools, which is not the nature of this device.
6. Standalone (Algorithm Only Without Human-in-the-Loop Performance) Study:
This concept is not applicable to the Poly Q impression materials, as they are physical materials used by a human practitioner, not an algorithm.
7. Type of Ground Truth Used:
Not explicitly stated. For "performance characteristics," the ground truth would likely be established through standardized physical and chemical property tests, rather than expert consensus, pathology, or outcomes data in the usual sense for diagnostic devices.
8. Sample Size for the Training Set:
Not applicable. As a physical impression material, there is no "training set" in the context of machine learning or AI.
9. How the Ground Truth for the Training Set Was Established:
Not applicable, as there is no training set for this device.
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