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Night Guard is indicated for protection against bruxism or nighttime teeth grinding. It creates a barrier between upper and lower dentition to protect the patient's overall occlusion.

Night Guards are designated to alleviate the pain and damage caused by bruxing or clenching the teeth. Severe tooth, jaw or facial muscle pains are common side effects of bruxing or clenching the teeth. These patients specific devices fit over upper or lower teeth during sleep and can offset the effects of bruxing or clenching, while protecting teeth from daily wear and tear. Night Guard is shipped non-sterile.

The provided text describes the acceptance criteria and the study that proves the "Night Guard" device meets these criteria. The study focuses on non-clinical performance tests to demonstrate substantial equivalence to a predicate device.

Here's the breakdown of the requested information:

1. Table of Acceptance Criteria and Reported Device Performance:

Additionally, Biocompatibility testing per ISO 10993-1 was passed for cytotoxicity, sensitization, acute systemic toxicity, subacute/subchronic toxicity, genotoxicity, and implantation.
Process Flow validation was performed to ensure that the finished device matches the software output specifications, and the Night Guard met these specifications.

2. Sample size used for the test set and the data provenance:
The document does not explicitly state the sample size for each test. However, for the "Toughness" test, the acceptance criteria mention "180 times of flexing cycles," and for "Wear Resistance," it mentions "10,000 cycles of abrasion," indicating the number of iterations or repetitions for these specific tests on material samples. The data provenance is not specified in terms of country of origin or whether it's retrospective or prospective; it appears to be internal testing conducted by 3D Diagnostix Inc.

3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts:
The document does not mention the use of experts or their qualifications for establishing ground truth for the performance tests. The "Rigidity" and "Fit" tests rely on visual examination and manual assessment, but the "expert" status is not defined.

4. Adjudication method (e.g., 2+1, 3+1, none) for the test set:
No adjudication method is mentioned for the test set.

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 MRMC comparative effectiveness study was done. This document describes the testing of a physical medical device (night guard), not an AI-assisted diagnostic tool.

6. If a standalone (i.e., algorithm only without human-in-the-loop performance) was done:
This question is not applicable as the subject device is a physical night guard, not an algorithm.

7. The type of ground truth used (expert consensus, pathology, outcomes data, etc.):
The ground truth for the performance tests (Rigidity, Toughness, Fit, Wear Resistance) is based on compliance with predefined acceptance criteria derived from internal requirements and/or relevant standards (ASTM D695, ISO 14569). It's a combination of objective measurements (e.g., compressive stress for toughness) and subjective assessment against established criteria (e.g., "feels sufficiently rigid," "stays on metal dentition when turned upside down" for fit). For biocompatibility, the ground truth is established by adherence to ISO 10993-1.

8. The sample size for the training set:
This section is not applicable. The Night Guard is a physical device, not a machine learning model, so there is no "training set."

9. How the ground truth for the training set was established:
This question is not applicable, as there is no training set for a physical device.

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The Night Guard is intended for protection against bruxism and nighttime teeth grinding. It is intended to reduce damage to teeth and to prevent the noise associated with bruxing and grinding.

NightGuard is a soft, comfortable, mouth guard intended to provide a barrier between the teeth for those patients who grind their teeth at night (bruxism). The product is shaped like a dental arch and is available in three sizes, but can be trimmed to fit more comfortably. NightGuard is a full coverage device which covers the occlusal surfaces of all the upper teeth.

The provided text describes a 510(k) submission for a non-diagnostic medical device (a mouth guard), not an AI/ML-enabled diagnostic device. Therefore, the typical acceptance criteria and study design elements requested in the prompt, which are relevant to AI/ML device performance evaluation, are largely not present in this document.

However, I will extract the information that is present concerning the device's "performance" in the context of this 510(k) submission.

1. Table of Acceptance Criteria and Reported Device Performance

For this medical device (NightGuard mouth guard), the "acceptance criteria" and "performance" are framed around substantial equivalence to predicate devices, rather than quantitative performance metrics like sensitivity or specificity. The primary "performance" characteristic is its ability to serve the intended use.

Study That Proves the Device Meets the Acceptance Criteria:

Based on the provided document, no specific study was performed to "prove" the device meets acceptance criteria in the context of performance metrics. For this 510(k) submission, the "proof" is established through a comparison to legally marketed predicate devices to demonstrate substantial equivalence.

Here's why and what was reported:

• Non-Clinical Tests Performed: "No non-clinical tests were preformed for the determination of substantial equivalence."
• Clinical Tests Performed: "No clinical tests were preformed for the determination of substantial equivalence."
• Conclusions Drawn From Non-Clinical and Clinical Tests: "No conclusions were drawn from Non-clinical and Clinical Test."
• Overall Conclusion: "NightGuard is as safe, as effective, and performs as well as or better than the predicated device." This conclusion is drawn purely from the narrative and tabular comparison of features with the predicate devices, not from direct testing of the NightGuard itself.

Given that this is a 510(k) for a non-diagnostic, non-AI device, the subsequent questions are not applicable. I will explicitly state why for each:

2. Sample size used for the test set and the data provenance (e.g. country of origin of the data, retrospective or prospective)

• Not applicable. No test set or data was used as no clinical or non-clinical studies were performed for this 510(k). The determination was based on comparison to predicate devices.

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. No test set was used, and therefore no ground truth was established by experts for performance evaluation.

4. Adjudication method (e.g. 2+1, 3+1, none) for the test set

• Not applicable. No test set was used.

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 device is not an AI/ML diagnostic. No MRMC study was performed.

6. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done

• Not applicable. This device is not an AI/ML algorithm.

7. The type of ground truth used (expert consensus, pathology, outcomes data, etc.)

• Not applicable. No ground truth was established as no performance studies were conducted. The "ground truth" for the 510(k) submission is the established safety and effectiveness of the predicate devices.

8. The sample size for the training set

• Not applicable. This is not an AI/ML device and does not have a training set.

9. How the ground truth for the training set was established

• Not applicable. This is not an AI/ML device and does not have a training set.

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