Efficacy of Er,Cr Laser incision Corticotomy in Rapid Maxillary Canine Retraction: A Split-Mouth Randomized Clinical Trial
Bibliographic record
Abstract
Introduction: This study sought to evaluate the efficacy of lasercision corticotomy for the acceleration of the canine movement. Our secondary objectives were assessing the canine rotation, the rate of anchorage control, the level of pain, and the gingival index (GI).Methods: Twelve orthodontic patients (9 females and 3 males) referring to the School of Dentistry and one dental clinic from May 2019 to September 2019 participated in this split-mouth randomized clinical trial. The allocation of the test and control sides was performed by flipping a coin. The mean age of patients was 18.91±3.87 years (range 15-30 years). The treatment plan included maxillary first premolar extraction. Following the initial leveling and alignment phase, an initial impression was made. Corticotomy was carried out with the erbium, chromium-doped yttrium scandium gallium garnet (Er, Cr: YSGG) laser (3.5 W, 30 Hz, 40% air, 80% water) in one maxillary quadrant (the laser side). Canine retraction was immediately initiated following surgery using nickel-titanium closed-coil springs with 150 g force. The impression was repeated 1 month after the onset of retraction. The casts were scanned, and the distance between the canine cusp tip and the rugae line was measured to quantify the amount of anteroposterior canine movement. The molar anchorage control was also evaluated by measuring the distance between the mesial contact of the permanent first molar and the rugae line. Gingival health was evaluated using the GI. The modified McGill pain questionnaire was used to assess the level of patients’ pain.Results: Lasercision corticotomy accelerated canine retraction with no adverse effect on gingival health. Anchorage loss in the posterior teeth and pain scores were not significantly different between the control and laser sides.Conclusion: Laser corticotomy can effectively accelerate canine retraction with no complications or discomfort for the patients.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 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".