Maxillomandibular Advancement for Obstructive Sleep Apnea in Patients With Obesity: A Meta‐Analysis
Bibliographic record
Abstract
OBJECTIVE: ) treated with maxillomandibular advancement (MMA). DATA SOURCES: Scopus, PubMed, CINAHL, and The COCHRANE Library. REVIEW METHODS: A search was performed from inception until April 3, 2024, in each database. RESULTS: A total of 14 studies (143 subjects) were included. The mean age was 44.3 years (range: 17-69), 80.2% males (95% CI: 72.5-86.5), mean BMI of 35.3 (95% CI: 33.1-37.5), and mean duration to follow-up post-MMA was 13.7 months (95% CI: 10.1-17.3). All objective outcomes improved significantly; overall, apnea-hypopnea index (AHI) decreased by -57.3 ([95% CI: -71.5 to -43.2], p < 0.0001) lowest oxygen saturation (LSAT) increased by 14.1% ([95% CI: 9.9 to 18.3], p < 0.0001), and Epworth Sleepiness Scale (ESS) decreased by -9.4 ([95% CI: -13.5 to -5.2], p < 0.0001). Surgical cure was 39.2% (95% CI: 20.3-60.0), and surgical success was 85.6% (95% CI: 77.8-91.5). Comparing percent reduction in class 3 obesity (-92.9%) as compared to class 1 (-85.5%) and class 2 (-83.6%) exhibited a significant difference (1 vs 3 p = 0.0012, 2 vs 3 p = 0.015). CONCLUSIONS: Our findings suggest that MMA significantly improves subjective and objective outcomes in OSA amongst patients with obesity with results comparable to the overall population. Success rates remained above 80% in studies with the highest mean BMI. In addition, patients with class 3 obesity yielded a significantly increased benefit based on percent reduction in AHI compared with class 1 and 2. LEVEL OF EVIDENCE: 1 Laryngoscope, 135:507-516, 2025.
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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 | 0.004 | 0.009 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.009 | 0.024 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 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".