Utility of Neck, Height, and Tonsillar Size to Screen for Obstructive Sleep Apnea among Obese Youth
Bibliographic record
Abstract
Objectives To determine whether neck:height ratio combined with adenoid and tonsillar size is a good predictive tool for obstructive sleep apnea in obese youth. Study Design Cross-sectional study. Setting Sleep clinics at the Hospital for Sick Children, Toronto, Canada. Subjects and Methods Consented obese individuals aged 8 to 18 years were recruited between 2013 and 2015. Anthropometric measures were obtained by a trained research coordinator in a standardized manner. Otolaryngologists evaluated adenoid and tonsil sizes. Obstructive sleep apnea was diagnosed with an overnight polysomnogram as an obstructive apnea-hypopnea index ≥2. Multivariable logistic regressions investigated the relationship between potential predictors and obstructive sleep apnea. The C-statistic measured the predictive ability. Results Of the 53 subjects (median age, 13 years; 55% males), 28 (53%) were diagnosed with obstructive sleep apnea, with a median index of 10.6 per hour. In a logistic regression controlling for adenoid size, enlarged tonsils were significantly associated with the presence of obstructive sleep apnea ( P < .01). Adding neck:height ratio into the model improved the model predictive ability (C-index increased from 0.73 to 0.84). Controlling for tonsil and adenoid sizes, an increase in neck:height ratio was significantly associated with the presence of obstructive sleep apnea ( P = .01). Conclusion Our study suggests that neck:height ratio combined with tonsillar hypertrophy may have a strong predictive ability for obstructive sleep apnea and may be useful in an ambulatory setting to screen obese youth at high risk. These findings should be confirmed in a larger study.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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".