Midline posterior glossectomy and lingual tonsillectomy in obese and nonobese children with down syndrome: Biomarkers for success
Bibliographic record
Abstract
OBJECTIVES/HYPOTHESIS: To examine outcomes following midline posterior glossectomy (MPG) plus lingual tonsillectomy (LT) for the treatment of significant obstructive sleep apnea (OSA) in children with Down syndrome (DS). METHODS: Patients with DS who had persistent OSA following tonsillectomy and adenoidectomy (TA) and were relatively intolerant of positive airway pressure (PAP) therapy were evaluated by physical examination and sleep/CINE magnetic resonance imaging to determine the etiology of upper airway obstruction. Patients with relative macroglossia underwent MPG plus LT if required. Successful surgical outcome was defined as the resolution of OSA or the ability to tolerate PAP. RESULTS: Thirteen children (8 male, 5 female), mean (standard deviation) age 14.2 (4.0) years underwent MPG plus LT. Fifty-four percent of patients were obese (Body mass index [BMI] > 95th centile) and 8% were overweight (BMI 85th-95th centile) preoperatively. All patients underwent pre- and postoperative polysomnography. Postoperatively, the obstructive apnea-hypopnea index fell significantly from 47.0/hour to 5.6/hour (P <.05) in normal weight individuals who did not become obese, but not in obese patients or those who became obese postoperatively. Successful surgical outcome was seen in all (N = 6) children who were normal weight or overweight preoperatively compared with none who were obese preoperatively (N = 7). CONCLUSION: Midline posterior glossectomy and LT are beneficial in normal weight and overweight children with DS who have persistent OSA following TA and are intolerant of PAP therapy. Obesity pre- or postoperatively portends a worse prognosis following MPG, suggesting that aggressive weight loss initiatives should be considered as an adjunct to surgery in this population. LEVEL OF EVIDENCE: 4. Laryngoscope, 127:757-763, 2017.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".