Craniofacial features of adult obese obstructive sleep apnoea patients in relation to the obesity onset – A pilot study
Bibliographic record
Abstract
INTRODUCTION: Obesity and craniofacial structures are aetiologies of obstructive sleep apnoea (OSA). The effect of obesity onset on the craniofacial development and growth of obese OSA subjects has been suggested, but supporting data were lacking. This study aimed to assess the craniofacial features of adult obese OSA patients in relation to their obesity onset. MATERIALS AND METHODS: A total of 62 adult OSA patients were included in the study, consisting of 12 early-onset (i.e. before puberty), 21 late-onset (i.e. after puberty) and 29 non-obese. All participants underwent a sleep study and cephalometric radiograph. Cephalometric analysis was conducted to measure the craniofacial features among the groups. RESULTS: The early obesity onset group (n = 12) showed a more prognathic mandible, longer lower facial height, protrusive incisors, a more caudal position of the hyoid bone and a wider lower airway. The late-onset group (n = 21) had more proclined and protrusive upper incisors, a shallower overbite, a more inferiorly positioned hyoid bone and an obtuse craniocervical angle. The overall obese group showed a combination of the findings above, plus a shorter soft palate and shorter airway length. There was no significant difference between early and late obesity onset groups. However, the early group showed a tendency for a shallower or decreased mandibular plane angle and deeper overbite. CONCLUSIONS: The current pilot study had many limitations but holds important information as a hypothesis generator. Craniofacial features of OSA patients with different obesity onset showed discrepancies and were distinguished from non-obese controls. Adult OSA patients with an early obesity onset showed a tendency for a more hypodivergent growth pattern than those with a late obesity onset.
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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 | 0.001 | 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".