LogoFDA 510(k) Search
K Number
K112868
Device Name
DREAMGARD REM-SOFT, DREAMGARD REM-LITE, DREAMGARD REM-ULTRA, DREAMGARD REM-MAX
Manufacturer
DREAMGARD, INC.
Date Cleared
2012-01-19

(111 days)

Product Code
MQC
Regulation Number
N/A
Type
Traditional
Panel
DE
Reference & Predicate Devices
K024261,K040315
Predicate For
N/A
AI/MLSaMDIVD (In Vitro Diagnostic)TherapeuticDiagnosticis PCCP AuthorizedThirdpartyExpeditedreview
Intended Use

Dreamgard nightguards are indicated for protection against bruxism (nighttime teeth grinding) and jaw clenching during sleep, short-term pain relief from muscle spasm due to occlusal interference, and prevention of chronic tension and temporal mandibular joint (TMJ) syndrome that is caused by chronic jaw clenching of the posterior mandibular and maxillary teeth by the temporalis muscle. Dreamgard nightguards are for prescription use only.

Device Description

The Dreamgard REM-SOFT, REM-LITE, REM-ULTRA and REM-MAX nightguards are composed of a soft, clear material made of thermoplastic resins. The devices are custom fabricated for each patient by taking an impression of the patient's upper teeth and using that impression to create a dental model to then fabricate a multi-layer custom nightguard using a pressure thermo-forming machine. The nightguard is designed to fit on the upper teeth and to span from 2nd molar to 2nd molar. The four versions of the Dreamgard nightguards differ in thickness based on the number of layers of thermoplastic resin used. The final custom product has a soft, comfortable inner layer and a harder protective outer layer. The dentist delivers the nightguard to the patient and provides final fitting and bite balancing adjustments by using the "boil and bite" method to mold the fit to the patient's teeth and bite.

AI/ML Overview

This document states that no performance data is required in support of the 510(k) notice for the Dreamgard Nightguards. Therefore, the device did not undergo performance testing to establish acceptance criteria or prove it meets them.

The 510(k) submission for the Dreamgard Nightguards relies on demonstrating substantial equivalence to predicate devices already on the market, rather than new performance studies. The key arguments for substantial equivalence are:

  • Intended Use/Indications for Use: Virtually identical to predicate devices.
  • Purpose and Functionality: Similar to predicate devices.
  • Physical Composition, Technological Characteristics, Design, and Principles of Operation: Similar to predicate devices, all composed of thermoformable resins.
  • Biocompatibility: Materials are commonly used in dental devices and biocompatibility testing shows they are safe.

As such, I cannot populate the requested table or answer the specific questions about performance study design, sample sizes, expert qualifications, or ground truth establishment.

A table of acceptance criteria and reported device performance cannot be generated as performance data was not required or provided.

Here's what can be stated based on the provided text:

  1. A table of acceptance criteria and the reported device performance:

    • No performance data or acceptance criteria are specified in the provided document. The submission relies on substantial equivalence rather than performance testing.

  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, as no performance study was conducted.

  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, as no performance study was conducted.

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

    • Not applicable, as no performance study was conducted.

  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 a physical dental appliance, not an AI-assisted diagnostic tool.

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

    • Not applicable. This device is a physical dental appliance, not a standalone algorithm.

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

    • Not applicable, as no performance study was conducted.

  8. The sample size for the training set:

    • Not applicable, as no performance study was conducted.

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

    • Not applicable, as no performance study was conducted.

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