Mandibular Distraction Osteogenesis vs. Tracheostomy in the Management of Pierre Robin Sequence: A Systematic Review and Meta-Analysis
Bibliographic record
Abstract
ObjectiveThis study compares mandibular distraction osteogenesis (MDO) and tracheostomy in managing severe airway obstruction in patients with the Pierre Robin sequence (PRS).DesignA systematic review and meta-analysis following PRISMA guidelines was performed. Literature searches were conducted across PubMed, ScienceDirect, Cochrane Library, Scopus, E.B.S.C.O., and Web of Science, including grey literature, covering studies until May 30, 2024. Study quality was assessed using the Newcastle-Ottawa Scale.Patientspatients with Pierre Robin Sequence.InterventionsMandibular distraction osteogenesis (MDO) and tracheostomy.Main Outcome MeasuresPrimary outcomes included airway management (tracheostomy avoidance for MDO, decannulation for tracheostomy) and feeding outcomes (G-tube placement). Secondary outcomes were hospital length of stay and associated costs.ResultsThirteen studies were included. MDO and the MDO-first approach demonstrated significantly better airway outcomes (OR = 10.72, 95% CI = 1.97-58.44, p = 0.006; OR = 4.51, 95% CI = 2.61-7.79, p < 0.00001). MDO also reduced the need for G-tube placement (OR = 0.09, 95% CI = 0.04-0.18, p < 0.00001) and lowered hospital costs (MD = -47.90 thousand USD, 95% CI = -59.93 to -35.87, p < 0.0001). A shorter hospital stay was observed but was not statistically significant.ConclusionsMDO offers better airway outcomes, lower G-tube placement rates, and reduced costs, making it a preferred option. Larger studies within the same syndromic status are needed to minimize confounding factors and validate these findings.
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 | 0.009 | 0.018 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.019 | 0.036 |
| Bibliometrics | 0.006 | 0.005 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 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".