Nonsurgical treatment of hemifacial microsomia by therapeutic ultrasound and hybrid functional appliance
Bibliographic record
Abstract
Aim: Conventional treatment of patients with hemifacial microsomia involves orthognathic surgery and/or distraction osteogenesis of the mandible. Previous reports showed that low-intensity pulsed ultrasound (LIPUS) enhances mandibular growth in growing rabbits and monkeys. In monkeys, LIPUS enhanced mandibular growth when combined with functional jaw orthopedic appliances. The purpose of this pilot study was to investigate if LIPUS could enhance mandibular growth in children with hemifacial microsomia. Methods: Five children (age range 3–11 years) with hemifacial microsomia were treated with hybrid jaw orthopedic functional appliances and treatment of the affected mandibular condyle by LIPUS for 20 minutes per day. Results: The results showed that after one year of treatment, significant improvement of the underdeveloped side of patients’ faces and mandibles was recognized both clinically and radiographically. Discussion: Although improvement took a longer time than did a surgical approach, optimizing this technique may achieve better results in a shorter treatment time. A randomized controlled clinical trial to investigate the effect of optimized LIPUS application or functional appliances in the treatment of hemifacial microsomia is warranted. Keywords: hemifacial microsomia, LIPUS, non-surgical treatment, children
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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 | 0.000 | 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) | 0.001 | 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".