Comparison of Epworth Sleepiness Scale and OSA‐18 Scores With Polysomnography in Children
Bibliographic record
Abstract
OBJECTIVE: Our goal is to determine if there is a correlation between Modified Epworth Sleepiness Scale (M-ESS) scores, obstructive sleep apnea (OSA)-18 scores, and polysomnography (PSG) outcomes in children. STUDY DESIGN: Retrospective chart review. SETTING: Pediatric otolaryngology clinic. METHODS: Charts of consecutive children presenting from July 2021 to July 2023 were reviewed. Demographics, body mass index (BMI), BMI Z score, M-ESS score, OSA-18 score, PSG results, and sleep apnea severity were included. One-way analysis of variance and Pearson/Spearman correlation coefficients were calculated. RESULTS: Three hundred sixty-seven children were included, 162 (44.1%) girls and 205 (55.9%) boys. Mean patient age was 7.8 (95% confidence interval [CI]: 7.3-8.3) years. M-ESS score was 6.3 (n = 348, 95% CI: 5.8-6.8), mean OSA-18 score was 56.2 (n = 129, 95% CI: 53.0-59.4). Mean apnea-hypopnea index (AHI) was 10.1 (95% CI: 8.7-11.4) events/h, obstructive AHI 9.3 (95% CI: 8.0-12.7) events/h, respiratory distress index 14.6 (95% CI: 8.4-20.8) events/h, and oxygen saturation nadir 89.8% (95% CI: 89.1-90.4). Sixty-two children (17.2%) had mild, 192 (53.5%) moderate, and 105 (29.2%) severe sleep apnea. M-ESS score correlated weakly to AHI (r = .19, P = <.001), and OSA-18 score to oxygen saturation nadir (r = -.16, P = .002). After logistic regression adjusted for age and BMI, neither clinical scores were independently associated with AHI. CONCLUSION: M-ESS and OSA-18 scores have a weak correlation with OSA severity in children. More reliable, age-appropriate screening tools are needed in pediatric sleep apnea.
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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 | 0.001 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".