Cephalometric Evaluation of Airways after Maxillary Anterior Advancement by Distraction Osteogenesis in Cleft Lip and Palate Patients: A Systematic Review
Bibliographic record
Abstract
OBJECTIVE: This study was conducted to review the changes in airways after maxillary anterior advancement by distraction osteogenesis in patients with cleft lip and palate. MATERIALS AND METHODS: Several electronic databases were searched. The selection criteria were set to include clinical trials and at least 1 year of postsurgical data. The original articles were then retrieved and evaluated by two investigators to ensure that they met the selection criteria. The references were also hand searched for possible missing articles. RESULTS: Forty-three abstracts were found in the electronic searches. After the first set of selection criteria was applied to these abstracts, 14 articles were retrieved. After the final selection criteria, only four articles were finally selected. However, sample sizes of the selected articles were small, and the methodological quality of the studies was inadequate. All selected articles were consistent in that upper airway sizes increased and nasal resistance was reduced after distraction osteogenesis. CONCLUSIONS: Despite the consistency of increasing the upper airway size and reducing nasal resistance in the only four found articles, limitations of the studies merit caution in interpreting these findings. We conclude that there are insufficient prospective randomized controlled clinical trials to confirm these results.
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 | 0.004 | 0.015 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.005 |
| Bibliometrics | 0.009 | 0.009 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".