Mean desaturation nadir values in children with sleep disordered breathing
Bibliographic record
Abstract
INTRODUCTION: Sleep studies are recommended in children suspected to have severe obstructive sleep apnoea (OSA) to stratify perioperative risk before adenotonsillectomy and to avoid unscheduled high-dependency unit admission. The mean desaturation nadir (MDN) is thought to be a useful measure of the overall hypoxic burden from sleep disordered breathing (SDB) events. MDN values have been reported in healthy children but not in those with severe OSA or other categories of SDB. METHODS: We report the findings of a cross-sectional observational study in children with SDB assessed with multichannel sleep studies (MCSS) in a UK secondary care centre between July 2022 and November 2024. We evaluated data from 1031 children recorded in a sleep study database, which is maintained for audit and service evaluation purposes. Following exclusions, the data of 889 children were analysed for MDN values according to SDB categories. The parameters measured with MCSS include oximetry, video, sound, movement, heart rate and pulse transit time but do not include airflow or an Apnoea-Hypopnoea Index (AHI) which is reported with cardiorespiratory studies or polysomnography. SDB categories were determined using oximetry and video criteria. RESULTS: We found that MDN falls with increasing severity of SDB, most notably in children with moderate and severe OSA. Approximately 4% of the cohort (n=37) had severe OSA (defined using McGill's criteria) and had a mean MDN of 88% (95% CI 87% to 89%). CONCLUSION: Our findings suggest that MDN values <90% can identify children with severe OSA who may have increased perioperative risk.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".