Assessment of the impact of vertical dimension alterations on the quality of sleep in elderly patients wearing upper and lower full dentures
Bibliographic record
Abstract
ABSTRACT Objectives: The loss of vertical dimension of occlusion (VDO) is a problem that affects stomatognathic system performance, mainly in edentulous patients. Thus, diseases related to musculature failure such as obstructive sleep apnea syndrome (OSAS) are common in these patients. Consequently, efficient and low-cost therapeutic strategies such as intraoral devices (IOD) used to expand the upper airway (UA) are needed to improve the quality of sleep in these patients. The aim of this study was to assess both the subjective and objective effect of VDO increase on the quality of sleep in 19 elderly patients using bimaxillary total prostheses (TPs) before and after placement of new TPs and therapy with intraoral devices (IOD) especially designed to increase VDO without causing mandibular advancement. Methods: For this purpose, questionnaires surveying quality of sleep (Epworth Sleepiness Scale, Pittsburgh Sleep Quality Index and sleep anamnestic questionnaire) and polysomnography tests (PSG) were performed at three different phases: baseline without TPs, with TPs and with IODs. Conclusions: It was concluded that the tested IODs may contribute to improvements in the quality of sleep for patients and their sleeping partners because they led to significant decreases in snoring. Most patients also expressed a preference for IOD use while sleeping. However, the use of IOD did not significantly improve polysomnography parameters compared to the baseline and thus cannot be indicated for the treatment of OSAS.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".