Clinical effectiveness of the Eruption Guidance Appliances in treating malocclusion in the mixed dentition: A systematic review and meta‐analysis
Bibliographic record
Abstract
AIM: To evaluate the clinical effectiveness of the eruption guidance appliances (EGAs) in treating malocclusion in the early mixed dentition. DESIGN: Electronic databases were comprehensively searched for the eligibility literature of the EGA treatment for a period spanning from the earliest available date in each database up to July 2021. Randomized controlled trials, controlled clinical trials, and prospective and retrospective cohort studies were included in the present review. The quality of clinical trials was assessed according to the Cochrane Collaboration's tools (RoB2.0 and ROBINS-I), whereas cohort studies were based on the Newcastle-Ottawa Scale (NOS). The data were gathered and synthesized with the Stata software (version 12). RESULTS: The screen yielded 436 articles, of which 17 papers were potentially eligible, and 7 articles from 3 studies (1 RCT, 1 CCT, and 1 PCS) were qualified for the final review and analysis. The meta-analysis showed both favorable dentoalveolar and skeletal changes in short term. Both overjet and overbite had a significant decrease after treatment (MD = -2.38 mm, 95% CI: -2.82 to -1.94, p < .001, and MD = -2.43 mm, 95% CI: -3.52 to -1.35, p < .001, respectively), and SNB increased significantly by 0.73 degrees (95% CI: 0.17-1.28, p = .01). After the retention period, however, overbite had a significant increase of 0.88mm, which indicated the occurrence of a relapse (95% CI: 0.60-1.16, p < .001). CONCLUSIONS: According to the existing evidence, the EGA treatment is effectively correcting overjet and overbite in the early mixed dentition in short term; furthermore, high-quality and long-term studies are warranted to determine its long-term effectiveness.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.010 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.004 | 0.003 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".