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The TD Clip is intended to be used with MATRx or MATRx plus Titration Trays to form a mandibular repositioning device intended to reduce or alleviate snoring and mild to moderate obstructive sleep apnea (OSA) in patients 18 years and older. The device is intended to be fitted with assistance from a healthcare professional and used during sleep for a total of less than 30 nights.

The TD Clip is a temporary oral appliance. The patient uses the temporary oral appliance to alleviate mild to moderate obstructive sleep apnea and/or snoring while waiting for a custom oral appliance to be manufactured. The dentist fabricates temporary titration trays consisting of upper and lower dental trays. The trays are custom fit to the patient using polyvinyl siloxane impression material. The healthcare provider may use the clip assembly to fasten the titration trays at the target therapeutic position to form the TD Clip temporary oral appliance. Patients may use the temporary oral appliance as treatment while waiting for their custom oral appliance. Adjustment of the position requires the setting of a new TD Clip by the healthcare professional.

The acceptance criteria and study proving the device meets them are described below for the TD Clip.

1. Table of Acceptance Criteria and Reported Device Performance:

2. Sample Size Used for the Test Set and Data Provenance:

• Sample Size: Not specified for any of the performance tests. The document only mentions "mechanical and environmental use conditions" and "repeated use and exposed to normal sleep forces over 30 nights of use".
• Data Provenance: The tests described are "Bench testing" and "simulated mechanical and environmental use conditions," indicating these were laboratory/engineering tests rather than human clinical trials. Thus, there is no country of origin or retrospective/prospective distinction for data provenance in the traditional sense; the data is from an engineering test setting.

3. Number of Experts Used to Establish the Ground Truth for the Test Set and Their Qualifications:

• Not applicable. The ground truth for these performance tests would be based on engineering specifications and direct measurements against those specifications, rather than expert interpretation of medical data. The evaluation was for mechanical and material performance.

4. Adjudication Method for the Test Set:

• Not applicable. Adjudication methods like 2+1 or 3+1 are used for clinical studies with human evaluators to establish ground truth for ambiguous cases. These were bench tests against predetermined engineering criteria.

5. If a Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study was done, and its effect size:

• No MRMC comparative effectiveness study was done. Clinical testing was explicitly stated as "not performed as the device has no technological differences from the predicate."

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

• Not applicable. The TD Clip is a physical medical device (an intraoral appliance) and not an algorithm or AI software. Therefore, the concept of "standalone performance" for an algorithm doesn't apply here. The performance tests focused on the physical integrity and function of the device itself.

7. The Type of Ground Truth Used:

• The ground truth for the performance testing was based on engineering specifications and predefined performance limits (e.g., no breakage, maintenance of protrusive positioning, quick and injury-free removal, adherence to biocompatibility standards). This is a form of objective, empirical measurement and adherence to established material and mechanical standards.

8. The Sample Size for the Training Set:

• Not applicable. As a physical medical device undergoing bench testing, 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.

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Overnight use of a temporary oral appliance to determine in which patients with obstructive sleep apnea mandibular advancement by an oral appliance will reduce obstruction of airflow and thereby to identify patients suitable for oral appliance therapy. The device is also used to recommend a target mandibular position that will reduce obstruction of airflow in patients determined to be suitable for oral appliance therapy.

The RCMP appliance is a device used in the clinical setting to identify patients with obstructive sleep apnea that will be successfully treated with an oral appliance. A temporary appliance fits to the patient's teeth and incrementally and reversibly advances the patient's mandible anteriorly with respect to the maxilla while the patient is under full polysomnographic monitoring. The repositioning of the mandible pulls the tongue forward and increases the patient's airway space. Such obstruction can be a causative factor in obstructive sleep apnea and snoring. The RCMP is used in the clinical setting by a technician to advance the mandible until the polysomnographic data indicates removal of the obstruction of airflow in the airway. The device is used to recommend a target mandibular position that will reduce obstruction of airflow in patients determined to be suitable for oral appliance therapy.

The RCMP appliance consists of upper and lower disposable dental titration trays that are used to hold onto the teeth by means of a quick-set retention material. The trays attach to a mandibular positioner that retracts and extends a rod to adjust the tray positioning by means of a small force linear actuator. By extending the linear actuator rod attached to the upper tray, the RCMP pushes on the upper teeth and pulls on the lower teeth, thus displacing the jaw. RCMP software interacts with the polysomnography to allow the technician to control fine adjustments of the relative position of the mandible.

Here's an analysis of the provided text to extract information about the acceptance criteria and the study proving the device meets them:

1. Table of Acceptance Criteria and Reported Device Performance

The provided text does not explicitly state quantitative acceptance criteria for the device beyond demonstrating that it is "at least as safe and effective as the predicate device at selecting candidates for oral appliance therapy." It highlights performance characteristics and differences from the predicate without setting specific numerical targets.

However, based on the qualitative descriptions and the overall goal of the study, we can infer some implied performance objectives:

2. Sample Size Used for the Test Set and Data Provenance

• Sample Size for Test Set: 66 patients.
• Data Provenance: The study was a prospective clinical study. Patients were recruited from a sleep center and dentist.

3. Number of Experts Used to Establish the Ground Truth for the Test Set and their Qualifications

The document mentions that:

• The RCMP is used "by a trained sleep technician".
• "The final assessment and recommendation for treatment by an appliance is completed by a physician who reviews the positioning data and associated cardio-respiratory reaction."
• The procedure was "user friendly to both the technician and the sleep expert."

While it confirms the involvement of a trained sleep technician for device operation and a physician (sleep expert) for final assessment and recommendation, it does not specify the exact number of physicians/sleep experts used to establish the ground truth (i.e., assess the suitability for oral appliance therapy and optimal mandibular position for each patient in the test set). It implies at least one physician. The qualifications are broadly described as "physician" and "sleep expert."

4. Adjudication Method for the Test Set

The document does not explicitly describe an adjudication method like 2+1 or 3+1 for establishing ground truth from multiple experts. It states that "the final assessment and recommendation for treatment by an appliance is completed by a physician who reviews the positioning data and associated cardio-respiratory reaction." This suggests a single physician's review is part of the process for determining the "therapeutically effective target protrusive distance" and identifying suitable patients, rather than a multi-expert adjudication of the ground truth itself based on labels provided by independent readers.

5. If a Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study was done, and its Effect Size

No, a Multi-Reader Multi-Case (MRMC) comparative effectiveness study comparing human readers with and without AI assistance was not done. The study focused on demonstrating the safety and effectiveness of the RCMP device itself, particularly its ability to identify suitable candidates and recommend an effective mandibular position, not on improving human reader performance.

6. If a Standalone (Algorithm Only Without Human-in-the-Loop Performance) was done

This device (RCMP) is not an AI algorithm but a physical, remotely controlled mechanical device. Its operation is explicitly stated to involve a "trained technician" and "physician" in a clinical setting. Therefore, a standalone (algorithm only) performance assessment is not applicable and was not performed. The device requires human interaction for its use and interpretation of its outputs.

7. The Type of Ground Truth Used

The ground truth used was based on polysomnographic data reviewed by a physician/sleep expert. Specifically, the device is used "in the clinical setting under full polysomnographic cardio-respiratory monitoring" to identify patients and then a "physician... reviews the positioning data and associated cardio-respiratory reaction" to make the final assessment and recommendation for treatment. This combines objective physiological measurements (polysomnography) with expert clinical judgment.

8. The Sample Size for the Training Set

The document does not mention a training set or its sample size. The clinical study described is a 66-patient validation study. Given that the RCMP is a device with mechanical and software components rather than a machine learning model, a distinct "training set" in the context of AI/ML is not relevant here. The device's design, software, and operational parameters would have been developed and tested through bench and engineering processes, not via a machine learning training dataset.

9. How the Ground Truth for the Training Set was Established

As no training set (in the ML sense) is mentioned, this question is not applicable. The device's functionality and efficacy were validated through the clinical study and bench testing, as opposed to being "trained" on a dataset.

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