Quality of Life and Subjective Outcomes Following Maxillomandibular Advancement Surgery for the Treatment of Obstructive Sleep Apnea
Bibliographic record
Abstract
Objective: The aim of this study was to assess outcomes related to general quality of life, daytime sleepiness and functional sleep outcomes, functional outcomes of orthognathic surgery, and facial aesthetics in patients undergoing maxillomandibular advancement (MMA) surgery for the treatment of obstructive sleep apnea (OSA).\nMaterials and Methods: This was a cross-sectional self-report study. A questionnaire was constructed using questions drawn from previously validated questionnaires. The survey was distributed to 25 patients who underwent MMA surgery for the treatment of OSA at LHSC in London, Ontario by a single surgeon between 2002 and 2013.\nResults: The survey results showed that MMA patients responded positively with respect to quality of life, snoring, functional sleep outcomes and daytime sleepiness, and facial aesthetics. Nineteen (86.4%) indicated that their sleep apnea symptoms have improved since the surgery. Eighteen (81.8%) reported neutral or positive changes with respect to facial attractiveness. Nineteen (86.4%) indicated that their overall quality of life has become better since having MMA. Most patients indicated that the surgery was worthwhile and would recommend it to others suffering from OSA.\nConclusions: MMA surgery for the treatment of OSA appears to have an overall positive effect on quality of life, sleep outcomes, and aesthetic outcomes. The majority of patients found the surgery worthwhile. Orthodontic treatment in conjunction with MMA appears to enhance the subjective aesthetic outcomes of treatment.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".