The role of oral appliance therapy in obstructive sleep apnoea
Bibliographic record
Abstract
There is now widespread recognition within the world of sleep medicine of the increasing importance of dental sleep medicine and, in particular, the role of oral appliance therapy (OAT) in the management of adults with obstructive sleep apnoea (OSA). For the purpose of this review, the term OAT refers to a custom-made intra-oral appliance, which acts to posture the mandible in a forward and downward direction, away from its natural resting position. Whilst nasally applied continuous positive airway pressure remains the “gold standard” in nonsurgical OSA management, OAT remains the recognised alternative treatment. This review of OAT aims to provide an evidence-based update on our current understanding of their mode of action, exploring the potential anatomical and physiological impact of their use in preventing collapse of the upper airway; the current clinical practice guidelines, including the recently published National Institute of Clinical Excellence 2021 guidance, in conjunction with the American Academy of Sleep Medicine and American Academy of Dental Sleep Medicine; optimal design features, comparing the role of custom-madeversusnoncustom OAT devices and the importance of titration in achieving a dose-dependent effect; patient predictors, preference and adherence to OAT; its impact on a range of both patient- and clinician-centred health outcomes, with a comparison with CPAP; the limitations and side-effects of providing OAT; and, finally, a look at future considerations to help optimise the delivery and outcomes of OAT.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".