(234 days)
The Narval Brux is intended for protection of teeth and restorations from the forces of bruxism.
The Narval Brux is a removable intraoral device used for protecting teeth and restorations aqainst the forces of bruxism. It consists of patient-specific splints that fit separately over the upper or lower teeth. The design of the splints is dependent on the patient needs.
The device functions as a protective barrier for teeth and restorations by creating physical separation between posterior occlusal surfaces and/or anterior incisal edges which will prevent tooth damage caused by grinding, bruxing and may help alleviate jaw and muscle pain.
The device is customized for each patient based on the clinician prescription.
The provided document is a 510(k) summary for the Narval Brux device, which is a mouthguard intended for the protection of teeth and restorations from bruxism.
The document does not describe a clinical study that proves the device meets specific acceptance criteria in the way a clinical trial for an AI/ML device would. Instead, this 510(k) submission establishes substantial equivalence to a predicate device (SomnoBrux Splint(s), K102909) through non-clinical testing.
Therefore, many of the requested categories for a study proving acceptance criteria cannot be directly answered from this document.
Here's an attempt to answer the questions based on the provided information, noting where information is not available due to the nature of the submission:
1. Table of Acceptance Criteria and Reported Device Performance
For the Narval Brux, the acceptance criteria are not presented as quantitative performance metrics (e.g., sensitivity, specificity) but rather as successful completion of non-clinical tests ensuring comparable safety and efficacy to a predicate device.
| Test Category | Acceptance Criteria | Reported Device Performance |
|---|---|---|
| Biocompatibility | Pass biocompatibility tests per ISO 10993 (cytotoxicity, sensitization). | Non-clinical data submitted included biocompatibility (cytotoxicity, sensitization per ISO 10993) and demonstrated substantial equivalence. |
| Software Validation | Software functions as intended and is safe. | Non-clinical data submitted included software validation and demonstrated substantial equivalence. |
| Cleaning Validation | Device can be effectively cleaned for reusable use. | Non-clinical data submitted included cleaning validation and demonstrated substantial equivalence. |
| Performance Testing | Withstand static compression forces representative of bruxism without failure to protect teeth. | Non-clinical data submitted included performance testing (static compression) and demonstrated substantial equivalence. |
| Substantial Equivalence | Demonstrate that the device does not raise new issues of safety or efficacy compared to the predicate device, based on similar Indications for Use, technological characteristics, and performance characteristics. | Based on the testing performed (biocompatibility, software validation, cleaning validation, and performance testing), it was concluded that the subject device does not raise new issues of safety or efficacy. The Narval Brux was assessed to be substantially equivalent to the predicate device (K102909). |
2. Sample size used for the test set and the data provenance (e.g. country of origin of the data, retrospective or prospective)
- Sample size for test set: Not applicable in the context of this 510(k) submission, as no human clinical test set (like an AI/ML model's test set) was used. The submission focuses on non-clinical engineering and material tests.
- Data Provenance: Not specified for the non-clinical tests. Non-clinical data typically refers to laboratory or bench testing.
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. Ground truth, in the AI/ML context, is not relevant for this type of non-clinical device submission. The "ground truth" here would be the validated performance of the materials and design against engineering standards.
4. Adjudication method (e.g. 2+1, 3+1, none) for the test set
- Not applicable. There was no test set requiring expert adjudication.
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
- No, a multi-reader multi-case (MRMC) comparative effectiveness study was not done. This type of study is relevant for AI/ML diagnostic or assistive technologies, not for a physical medical device like a mouthguard, especially when establishing substantial equivalence via non-clinical data.
6. If a standalone (i.e. algorithm only without human-in-the loop performance) was done
- Not applicable. This is not an AI/ML algorithm.
7. The type of ground truth used (expert consensus, pathology, outcomes data, etc.)
- The "ground truth" or basis for evaluation in this submission stems from established engineering standards, material safety standards (ISO 10993 for biocompatibility), and performance test methodologies (static compression) for mouthguards. The substantial equivalence argument relies on the new device performing equivalently to the predicate device in these non-clinical aspects.
8. The sample size for the training set
- Not applicable. There is no AI/ML training set mentioned in this document.
9. How the ground truth for the training set was established
- Not applicable. There is no AI/ML training set described.
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