Outcome following Surgical Interventions for Micrognathia in Infants with Pierre Robin Sequence: A Systematic Review of the Literature
Bibliographic record
Abstract
BACKGROUND: Tongue-lip adhesion (TLA), mandibular distraction osteogenesis (MDO), and subperiosteal release of the floor of the mouth (SPRFM) are the most commonly performed surgical procedures to treat severe airway obstruction in infants born with Pierre Robin sequence (PRS). OBJECTIVES: To determine the rate of failure of each type of procedure, in terms of mortality and the need for tracheostomy, and to determine what proportion of infants have significant airway obstruction postoperatively as determined by polysomnography (PSG) and compare the data by procedure type. METHOD: A comprehensive literature search (1981 through June 2015) was done of the National Library of Medicine database using PubMed. Extracted data included diagnosis, type of surgery, and outcome including mortality, need for postoperative tracheostomy and details of PSG. Persistence of significant airway obstruction was defined as an apnea-hypopnea index >15 events/h on PSG. RESULTS: Both mortality rate and need for tracheostomy were low for all procedures. Many studies lacked sufficient detail to identify significant airway obstruction postoperatively. In studies with sufficient data, MDO was associated with the lowest percentage of significant airway obstruction postprocedure (3.6%) compared to 50% for infants who underwent TLA. Insufficient PSG data was available for patients who were treated with SPRFM. CONCLUSIONS: There is a paucity of objective PSG data to definitively assess postoperative airway outcomes for PRS. MDO appears to be the most effective technique based on the available PSG data. Standardized use of PSG may lead to better identification and treatment of patients at risk for suboptimal airway outcomes postoperatively.
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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 | 0.003 | 0.019 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.004 |
| Bibliometrics | 0.011 | 0.011 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| 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".