Effectiveness of interceptive treatment of class III malocclusions with skeletal anchorage: A systematic review and meta-analysis
Bibliographic record
Abstract
Recently, new strategies for treating class III malocclusions have appeared. Skeletal anchorage appears to reduce the dentoalveolar effects while maximising the orthopaedic effect in growing patients. The purpose of this systematic review and meta-analysis is to examine the effectiveness of bone anchorage devices for interceptive treatment of skeletal class III malocclusions. Searches were made in the Pubmed, Embase, Scopus and Cochrane databases, as well as in a grey literature database, and were complemented by hand-searching. The criteria for eligibility were: patients who had undergone orthodontic treatment with skeletal anchorage (miniplates and miniscrews). Patients with syndromes or craniofacial deformities or who had undergone maxillofacial surgery were excluded. The following variables were recorded for each article: author, year of publication, type of study, sample size, dropouts, demographic variables, treatment carried out, radiographic study (2D or 3D), follow-up time, and quality of the articles on the Newcastle-Ottawa Scale. The means and confidence intervals of the following variables were employed: Wits, overjet, ANB, SNA and SNB. Initially, 239 articles were identified. After removing the duplicates and applying the selection criteria, 9 were included in the qualitative synthesis and 7 in the quantitative synthesis (meta-analysis). It may be concluded that skeletal anchorage is an effective treatment for improving skeletal Class III malocclusion, but when compared with other traditional treatments such as disjunction and face mask, there is no clear evidence that skeletal anchorage improves the results.
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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 | 0.017 | 0.031 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.019 | 0.037 |
| Bibliometrics | 0.007 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".