Can antegonial notch angular measurements on lateral cephalometry be used to monitor children following TMJ ankylosis treatment?
Bibliographic record
Abstract
Objective This research aims to introduce using antegonial notch angular measurements on lateral cephalometry as a simple low-dose radiographic approach for monitoring mandibular growth in children after TMJA treatment.Methods This retrospective cohort study used dental records to identify eligible patients: healthy children with true unilateral TMJA who underwent conservative gap arthroplasty followed by post-operative physiotherapy. The primary outcome was changes in antegonial notch angular measurements over time. Secondary outcomes included correlations between antegonial notch angular measurements and two growth-related conventional cephalometric angles (SNB and ANB). We also explored the relationship between changes in antegonial notch angle over time and study covariates.Results Eleven patients aged 4 to 9.5 years with unilateral bony TMJA for periods ranging from 9 to 20 months who had undergone conservative gap arthroplasty followed by physiotherapy were included. Significant increases were observed in antegonial notch angles on both the affected and non-affected sides after treatment (p < .05), indicating resumed mandibular growth. Although the affected side remained significantly smaller than the non-affected side at both timepoints (p= 0.033 and 0.005), asymmetry did not change significantly over time (p= 0.273), suggesting parallel bilateral growth. Positive correlations were found between antegonial notch changes and SNB (p= 0.039–0.047). Multivariate regression indicated that TMJA duration significantly influenced changes in the affected-side notch angle (p= 0.004).Conclusion Based on these preliminary data, antegonial notch angular measurements on lateral cephalometric radiographs may offer a simple, reliable, and low-radiation alternative for monitoring mandibular growth in children after TMJA treatment. Further studies with larger sample sizes are required to support our findings.
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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 | 0.002 | 0.006 |
| 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 | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| 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".