Skeletal and dental effects of Herbst appliance anchored with temporary anchorage devices: A systematic review with meta‐analysis
Bibliographic record
Abstract
BACKGROUND: The aim was to evaluate the efficiency of using temporary anchorage devices (TADs) in minimizing the anchorage loss and increasing the skeletal effects during correction of Class II malocclusion with Herbst appliance. MATERIALS AND METHODS: Search without restrictions was performed up to January 2021 in three electronic databases (CENTRAL, MEDLINE and EMBASE) for randomized controlled trials (RCTs), prospective and retrospective cohort studies. The included studies assessed the dental and skeletal changes in Class II malocclusion patients who were treated using Herbst appliance with or without TADs. The strength of evidence was ranked using GRADE. RESULTS: Fifty-five records were initially retrieved. A total of 6 studies with 198 patients were finally considered. 4 studies were included in the meta-analysis. The meta-analysis showed that using TADs with acrylic splint Herbst appliance was effective in controlling the inclination of mandibular incisors by a mean difference of -5.49 degrees (95% C.I [-7.36, -3.63], P < .001) when compared to Herbst appliance alone. The results showed also that incorporating TADs with Herbst treatment resulted in greater mandibular skeletal effects including increasing mandibular bone base length by mean difference of 2.22 mm (95% C.I [0.82. 3.61], P = .002) and mandibular length by mean difference of 3.7 mm (95% C.I [1.55, 5.85], P < .001) when compared to Herbst appliance alone. CONCLUSIONS: Based on a very low level of confidence, it seems that incorporating TADs during orthodontic treatment with Herbst appliance results in minimizing the anchorage loss and increasing the skeletal effects of Herbst appliance during correction of Class II malocclusion.
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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 | 0.011 | 0.020 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.017 | 0.036 |
| Bibliometrics | 0.008 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".