Evaluation Mandibular Advancement Surgeries For Pediatric Obstructive Sleep Apnea: A Systematic Review And Meta-Analysis
Bibliographic record
Abstract
Background and aim: Obstructive sleep apnea syndrome is a common condition in children. The aim of current Systematic Review and Meta-Analysis study was evaluation Mandibular Advancement Surgeries for Pediatric Obstructive Sleep Apnea. Method: From the electronic databases, PubMed, Scopus, LILACS, Web of Science, EBSCO, LIVIVO, and Embase have been used to perform a systematic literature over the last ten years between 2011 and May 2021. Newcastle-Ottawa Scale and Cochrane Collaboration’s tool used to assess quality of the cohort studies and randomized control trial studies, respectively. Mean difference with 95% confidence interval (CI), fixed effect model and Inverse-variance method were calculated. Random effects were used to deal with potential heterogeneity and I2 showed heterogeneity. I2 values above 50% signified moderate-to-high heterogeneity. The Meta analysis have been evaluated with the statistical software Stata/MP v.16 (The fastest version of Stata). Result: In the first step of selecting studies 4571 studies were selected to review the abstracts, in the second step, the full text of 114 studies was reviewed. Finally, eleven studies were selected. Meta-analysis reported reduction Apnea-hypopnea index, mean difference between preoperative Apnea-hypopnea index and postoperative Apnea-hypopnea index was -2.11 events/h (MD, -2.11 95% CI -2.35, -1.87; P= 0.00) among the eleven studies. Conclusion: change in Apnea-hypopnea index after mandibular advancement surgeries was -2.11 events/h reduction. Studies with long-term outcomes are needed.
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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 | 0.011 | 0.023 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.017 | 0.043 |
| Bibliometrics | 0.009 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| 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".