Comparison of relapse of orthodontic treatment following aligner versus conventional fixed appliance treatment. A systematic review
Bibliographic record
Abstract
Background: Aligners are an alternative that are currently being widely used in orthodontic treatment, however, post-treatment relapse following aligner versus conventional treatment has not been compared. The objective of this study was to compare post-treatment relapse of orthodontic treatment with dental aligners versus conventional fixed orthodontics through a systematic review. Material and Methods: An exhaustive search was carried out in the MEDLINE (via PubMed), EBSCO, SCOPUS and EMBASE databases up to September 30, 2023. A total of 522 articles were found and after applying the selection criteria, the full texts of 24 articles were chosen for evaluation. At the end of the evaluation, only 3 studies were considered, two observational studies and one randomized clinical trial. The Newcastle Ottawa and Risk of bias (ROB-2) tools were used to assess the risk of bias. Results: >0.05). In addition, the two latter studies reported slight relapse related to detachment of the fixed retainer. Conclusions: Aligners, brackets, relapse, orthodontic.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.007 | 0.025 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.009 | 0.008 |
| Bibliometrics | 0.009 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".