Short‐ and long‐term potential effects of accelerated osteogenic orthodontic treatment: A systematic review and meta‐analysis
Bibliographic record
Abstract
OBJECTIVE: To better understand the potential effects after corticotomy accelerated osteogenic orthodontic treatment (CAOOT). SETTING AND SAMPLE POPULATION: Systematic review with meta-analysis. MATERIALS AND METHODS: A literature search up to August 2018 was conducted to identify randomized clinical studies (RCTs) on CAOOT reporting periodontal parameters, bone changes, patient-centred and short- and long-term adverse outcomes. A random-effects meta-analysis was performed on various parameters (bone density, buccal bone thickness, anchorage loss, visual analog scale, root resorption and retraction time) to quantify weighted treatment effects. RESULTS: A total of five split mouth, four parallel arms, one regular RCTs and two prospective CCTs were included (206 patients). Pooled data showed increase in bone thickness by 0.68 mm (95% CI: 1.17, 0.19) and reduced retraction time by 2.80 months (95% CI: -4.17, -1.43). There were statistically insignificant differences for root resorption 0.24 mm (95% CI: -0.49, 0.96), anchorage loss 0.49 mm (95% CI: -1.38, 0.40), worsening of periodontal parameters (gingival index) by 0.30 (95% CI: -0.83, 0.23) and mean increase in bone density of 7.07% on the corticotomy side at 6 months (95% CI: -3.24, 17.38). CONCLUSION: Current evidence suggests a very low to low level of certainty (GRADE assessment) in regard to quantified effects after CAOOT. Although CAOOT procedures show insignificant increase in the density following the use of bone graft and anchorage loss, they appear to accelerate the tooth movement during the first few months, to increase the buccal bone thickness and to show good tolerance by the patients; the clinical significance of these changes may be considered questionable.
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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 | 0.014 | 0.031 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.018 | 0.039 |
| Bibliometrics | 0.005 | 0.005 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| 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".