Airflow Analysis of the Upper Airway in Skeletal Class II Growing Patients with Constricted Maxilla Treated using Twin Block and Hyrax
Bibliographic record
Abstract
Sleep-breathing disorders (SBD) affect individuals on a global scale, encompassing a spectrum of conditions with obstructive sleep apnea (OSA) and snoring at the extremes. The prevalence of OSA in children is estimated to be between 1-5%. In patients with OSA, episodes of hypopnea (partial breathing cessation) or apnea (complete breathing cessation) can occur multiple times during sleep, leading to chronic hypoxia and various health issues, including hypertension, cardiovascular diseases, impaired growth, behavioral problems, and reduced quality of life. While nocturnal polysomnography is the gold standard for OSA diagnosis, its high cost and long wait times limit accessibility, particularly in Canada, where the demand for testing significantly exceeds capacity.Certain oral anatomical features, such as a high-arched or narrow upper jaw and retruded lower jaw, may be linked to pediatric OSA, making dentists potential early screeners. Treating OSA requires a multidisciplinary approach, with sleep physicians overseeing diagnosis and dentists managing oral appliances that aid treatment in selected cases. Orthodontic interventions, including mandibular advancement and maxillary expansion, aim to improve localized upper airway dimensions. For instance, the Hyrax appliance facilitates maxillary expansion, potentially enhancing nasal airflow, while the Twin Block appliance positions the mandible forward, which may increase oropharyngeal space. The actual impact of those increases on breathing function is still controversial.This research investigated the relationship between upper airway (UA) dimensions, inspiratory flow, airway resistance, and SBD-related questionnaires in children undergoing maxillary expansion and Class II malocclusion mandibular corrector devices. Additionally, it explored whether UA volume changes correlate with airway resistance changes. The primary objectives included developing a segmentation technique for volumetric analysis of the UA, validating a pressure drop experimental analysis, and assessing airflow changes before and after orthodontic interventions. Additionally, this study aimed to determine whether the order of treatment influences UA and airflow changes, increasing our understanding of the impact of orthodontic treatment on some UA parameters.The research hypotheses posit that mandibular protrusion and maxillary expansion will lead to observable changes in UA dimensions and airflow. The study tested the null hypotheses regarding the lack of airflow changes post-treatment and the absence of correlations among various measured parameters. Ultimately, this work aimed to enhance understanding of orthodontic impacts on upper airway dynamics and airflow resistance, potentially informing better treatment strategies for OSA in children.Thirty-two participants were analyzed, 10 in control, 12 in Hyrax, and 10 in Twin Block groups. The mean age at T1 was 10.4 years of age and at T3 was 12.1 years of age. 75% of the hyrax group was female, 20% of the twin block groups were female and 60% of the control group was female. The mean treatment time was 1.7 years. Results showed that the Hyrax group had a mean decrease in air resistance of 0.4 cmH2O/L/s, a mean increase in peak nasal inspiratory flow of 20 L/min, a mean increase in peak oral inspiratory flow of 51L/min, a mean volume increase of 10.7 cm3, a mean minimal cross-sectional area increase of 86 mm2. All these measurements were statistically significant (p<0.05). The Twin Block group showed statistically significant results in peak oral inspiratory flow with a mean increase of 45L/min and a volumetric mean increase of 11.9cm3. The control group showed statistically significant results in peak nasal inspiratory flow with an increase of 30L/min.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".