App-Based Myofunctional Therapy to Improve Adherence and Outcomes of Mandibular Advancement Devices in Moderate Obstructive Sleep Apnea: Multicenter Randomized Trial Protocol
Bibliographic record
Abstract
Background: Mandibular advancement devices (MADs) are a valid alternative for patients with moderate obstructive sleep apnea (OSA) who do not tolerate continuous positive airway pressure. Despite their efficacy, both adherence and long-term results remain a challenge. Myofunctional therapy (MT) has shown potential to improve upper airway muscle tone and reduce OSA severity, but its role as an adjunct to MAD treatment is still unclear. This protocol evaluates whether app-based MT (Airway Gym) can improve adherence and clinical outcomes in patients with moderate OSA treated with MADs. We describe the study design. Objective: This study aims to evaluate whether a mobile app-based MT program (Airway Gym) can improve adherence to MAD therapy and related sleep parameters in patients with moderate OSA treated with MADs. Methods: This multicenter, prospective, randomized, controlled study included adults aged 18-75 years with moderate OSA (apnea-hypopnea index 15-30). Participants were randomized into four groups: (1) placebo exercises, (2) MT only, (3) MAD only, and (4) MAD plus MT. Outcomes included changes in the apnea-hypopnea index, oxygen desaturation index, sleep quality (Epworth and Pittsburgh scores), and tongue strength/endurance measured with the Iowa Oral Performance Instrument and a tongue digital spoon. Adherence was monitored via telemedicine and sleep diaries. Results: Recruitment began in February 2024 across participating centers. Data collection was planned to continue until December 2025, after which the final analyses were performed. The protocol described the study procedures up to the most recent administrative review conducted in January 2025. Conclusions: This protocol describes the rationale and methodology of a randomized trial evaluating app-based MT as an adjunct to MAD therapy in patients with moderate OSA. Full study results will be reported after the final analysis.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.008 | 0.009 |
| Meta-epidemiology (narrow) | 0.004 | 0.002 |
| Meta-epidemiology (broad) | 0.006 | 0.004 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.004 | 0.004 |
| Insufficient payload (model declined to judge) | 0.031 | 0.004 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".