Comparing a sibilant phoneme denture bite position with an anterior protrusive mandibular positioning device in oral appliance therapy for dental treatment of obstructive sleep apnea: A systematic review
Bibliographic record
Abstract
Objective: The objective of this systematic review is to provide a summary of the published literature related to the use of a sibilant phoneme technique (SPT) for determining mandibular positioning in dental sleep appliances for the management of obstructive sleep apnea (OSA), and to summarize these findings into normative ranges and protocols similar to those already established for anterior protrusive mandibular positioning.Methods: A search was performed on five databases: MEDLINE, Embase, Cochrane Library, Scopus, and Web of Science Core Collection.Articles not related to sleep medicine and dentistry were excluded.Only articles with a high likelihood of using a sibilant phoneme/phonetic and/or biomimetic occlusal registration with presleep and postsleep testing were selected.Review of the selected articles did not justify a meta-analysis.Results: Six articles met the loose inclusion criteria, of which only three articles met strict inclusion criteria.Of these three articles, two included deliberate maxillary expansion precluding the results from comparability with other mandibular positioning techniques.The remaining article was a direct comparison of the number of titrations between a SPT and a George Gauge anterior protrusive technique for mandibular positioning for dental sleep appliances.Conclusions: Insufficient information exists on the use of the SPT for mandibular positioning in dental sleep appliances for the management of OSA.Because of the potential for a therapeutic outcome with minimal protrusion of the mandible and therefore lower risk of developing the side effects associated with dental sleep appliances, further research should be explored in this area.
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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 | 0.007 | 0.028 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.010 | 0.011 |
| Bibliometrics | 0.006 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.000 |
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".