Rapid maxillary expansion and its impact on sleep apnea in children aged 5 to 8 years: a retrospective study
Bibliographic record
Abstract
OBJECTIVE: Determine the impact of early transverse maxillary expansion on the symptomatic manifestation of sleep apnea in children aged 5-8 years. METHODS: Nineteen patients (mean age: 6.84 years) with maxillary constriction underwent rapid maxillary expansion (RME) for orthodontic treatment. Inclusion criteria: age 5-8 years, Apnea-Hypopnea Index (AHI) > 1, treated with Memory screw Hyrax appliance, under pediatric sleep physician care. Exclusion criteria: non-compliance, re-evaluation delays (> 3 months). Primary variable: AHI before (T0) and after (T1) expansion. Treatment ended based on malocclusion correction. AHI comparisons included dentition status and gender as secondary variables. RESULTS: A paired t-test showed no significant difference in the mean AHI between T0 (4.05±2.55) and T1 (3.68±3.12) for primary variables (p>0.05). At T0, no significant AHI difference was found between genders (F: 3.21±2.47; M: 4.09±2.87, p>0.05). After expansion (T1), a significant change was observed between genders (F: 1.75±1.03; M: 5.18±3.68, p<0.05). There was also no significant difference in AHI changes based on dentition status. A negative correlation was found between AHI changes and transverse changes and at canine and molar levels. CONCLUSION: No significant evidence was found to support the effectiveness of early maxillary expansion in improving sleep apnea among children with maxillary constriction. However, the gender-specific responses and the potential dose-response relationship between maxillary expansion and AHI reduction highlight the complexity of treating pediatric OSA.
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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 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.002 | 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".