Velopharyngeal Space Assessment in Patients Undergoing Le Fort 1 Maxillary Advancement
Bibliographic record
Abstract
Background: The effects of maxillary advancement on velopharyngeal anatomy have primarily been studied using lateral cephalometric radiographs. However, with recent advances in orthognathic surgery, there is an increased need for more detailed and precise imaging such as computerized tomographic (CT) scan reconstructions, to help in surgical planning and to measure outcomes. The purpose of this study was to compare the pre- and post-operative velopharyngeal anatomic configuration modifications as measured on CT scans. Methods: This is a retrospective cohort study of 44 patients with and without cleft palate who were treated with maxillary advancement. The pre- and post-operative CT scans were compared with respect to pre-established landmarks. Linear distances, cross-sectional areas, and volumes were measured using 3-dimensional CT scan reconstructions. Results: For the linear distances measured, a statistically significant difference was found when comparing the pre- and post-operative measures of the narrowest part of the nasopharynx and the narrowest part of the retropalatal airway space (P = 0.001 and 0.026, respectively). Retropalatal cross-sectional areas, nasopharyngeal cross-sectional areas, and the volumetric assessment of the nasopharyngeal space showed no statistically significant differences when comparing pre- and post-operative scans (P < 0.05). Mean changes in the measures did not differ over time (pre- and post-operative) depending on whether there was a prior history of cleft palate repair. Conclusions: Although structural modifications of the pharyngeal space are inherent to maxillary advancement, its surface area and volume do not significantly change. The use of 3-dimensional reconstruction using CT scans should be the first choice for evaluation of the upper airway.
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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 | 0.001 |
| 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".