Evaluation of Two Mini-implant Lengths in the Infrazygomatic Crest Region: A Randomized Clinical Trial
Bibliographic record
Abstract
Abstract Objective Temporary anchorage devices (TADs) have revolutionized fixed orthodontic appliance treatment through anchorage controlling in the clinic and play an essential role in resolving many complex cases. Due to the limited space, there is a risk of injury to the roots while using interradicular microimplants. Therefore, the infrazygomatic crest (IZC) area can be an alternative mini-implant insertion site in the maxillary arch. The aim of the study was to evaluate the primary stability, pain perception, sinus penetration, late stability, and failure rate with two mini-implant lengths in the IZC area. Materials and Methods Forty-eight mini-implants (Tusk Dental Co., Ltd., Canada) with two different lengths (length/diameter: 12/2 and 14/2 mm) were grouped by length (24 per group) and inserted bilaterally into the IZC area of 24 patients. The data were statistically analyzed, considering a significance level of p < 0.05. Results Sinus penetration prevalence did not differ significantly between 12-mm (54.2%) and 14-mm (62.5%) mini-implants (p > 0.05). Primary stability was significantly higher with the 14-mm mini-implants (p < 0.05). The failure rate did not differ significantly between the 12-mm (20.8%) and 14-mm (16.7%) mini-implants (p > 0.05). Conclusion While the failure rate was similar between 12- and 14-mm mini-implants, the 14-mm mini-implants were more likely to damage adjacent structures. Therefore, shorter mini-implants should be preferred over longer mini-implants for most cases requiring IZC TADs. Trial Registration ID ClinicalTrials.gov identifier: NCT06293872.
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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 | 0.005 | 0.004 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.003 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".