Impacted and transmigrant mandibular canines incidence, aetiology, and treatment: a systematic review
Bibliographic record
Abstract
Background: The incidence of impacted and transmigrant mandibular canines in the mandible is not as high as that in the maxilla; consequently, it is more difficult to find clinical guidelines derived from sound studies based on large patient samples. Objectives: The aim of this systematic review was to summarize currently available data pertaining to the incidence and aetiology of impacted and transmigrant mandibular canines and the success rates of different treatment strategies. Methods: This review was registered with PROSPERO (CRD42014006175) and was conducted using PRISMA and CRD (Centre for Reviews and Dissemination, University of York) statement. A computerized search of studies published up to February 2016 was conducted using the following databases: PubMed, Cochrane Central Register of Controlled Clinical trials, ISI Web of Knowledge, and Scopus. To identify any relevant publications not included in this list, we manually searched the references lists of the selected articles. The Newcastle-Ottawa Scale quality assessment tool was utilized to classify the included articles. Results: In total, 630 articles were identified after the removal of duplicates. A total of 13 studies published between 2001 and 2015 met all the eligibility criteria and were included for the final analysis. The sample size in these studies ranged from 14 to 112873 teeth, while their methodological quality ranged from low to medium. Conclusions: According to the findings from our review, the incidence of canine impaction in the mandible ranges from 0.92 to 5.1 per cent, while that of canine transmigration ranges from 0.1 to 0.31 per cent. Various etiologies may play a role, including odontomes (up to 20 per cent) and lateral incisor anomalies (16 per cent). Surgical extraction (89 per cent in some studies) and orthodontic traction (20-32 per cent) are the most commonly used treatment strategies, with the latter showing a failure rate of 17 per cent in two studies.
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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 | 0.008 | 0.041 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.008 | 0.007 |
| Bibliometrics | 0.012 | 0.013 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.002 |
| 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".