Evaluation of Mandibular Projection in Class II Division 2 Subjects Following Orthodontic Treatment Using Clear Aligners
Bibliographic record
Abstract
Aim: The purpose of this study was to evaluate the mandibular growth and/or projection following maxillary incisor proclination, overbite correction, and maxillary dentoalveolar expansion without the use of any class II mechanics, in growing class II division 2 patients treated with clear aligners.Materials and methods: Before and after treatment cone-beam computed tomographic (CBCT) generated lateral and posteroanterior cephalograms of thirty-two patients with skeletal class II division 2, 16 in the treatment group and 16 in the untreated group, were reviewed to evaluate treatment-related changes.Upper incisors were proclined and protruded, as well as upper arch expansion and overbite correction were performed as part of their regular treatment.Cephalometric analysis was performed to evaluate skeletal and dental changes.Unpaired statistical t-tests were performed to determine if significant skeletal class II correction was achieved in the treatment group.Results: In the treatment group, after treatment, the upper incisors became more proclined and protruded, and the inter-molar width increased while the overbite was reduced compared to the control group.An increase in skeletal mandibular growth and forward projection was also observed, thus contributing to an improvement of the sagittal skeletal relationship as evidenced by ANB and Wits values compared to the control group.Conclusion: A combination of upper incisor proclination, correction of deep overbite, and maxillary dentoalveolar expansion using clear aligners appears to contribute to an improvement of the skeletal class II relationship in growing patients with class II division 2. Clinical significance: This study shows that unlocking the mandible by correcting a deep overbite, proclining upper incisors, and expanding the upper arch in growing class II division 2 patients can improve skeletal class II using clear aligners.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".