Focus of dental sleep medicine on obstructive sleep apnea in older adults: A narrative review
Bibliographic record
Abstract
PURPOSE: To review dental sleep medicine in older adults based on the literature. STUDY SELECTION: This narrative review focuses on sleep physiology, common sleep disorders, and obstructive sleep apnea (OSA) in older adults and their management. RESULTS: Sleep physiology differs between older and younger adults, with sleep disturbances occurring more frequently in older adults. The prevalence of insomnia increases in older adults due to age-related changes in sleep physiology. Insomnia, sleep-disordered breathing, periodic limb movement disorder, restless legs syndrome, and rapid eye movement (REM) sleep behavior disorder are common sleep disorders in older adults. OSA is more prevalent in older adults, and its effects on them are considered more substantial than those on younger adults. The treatment of older patients with mandibular advancement devices may be less effective and more complex owing to potential impairments in oral and dental health. Furthermore, the prevalence of edentulism in older adults is decreasing while life expectancy is increasing. CONCLUSIONS: As older adults have comorbidities that affect sleep quality, dentists should consider the effects of sleep physiology and sleep disorders in these patients. OSA may decrease the quality of life and increase the risk of developing other diseases. Therefore, dentists proposing treatment with mandibular advancement devices need to inform patients of their potential lack of efficacy and the requirement for careful follow-up owing to known and unknown side effects.
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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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.005 | 0.004 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".