Obesity and obstructive sleep apnea in children less than eight Years of age
Bibliographic record
Abstract
Obstructive sleep apnea complicates obesity. The number of obese children < 8 years of age is increasing. Our aim was to describe the polysomnographic findings of obese children < 8 years of age and compare these to lean children. We retrospectively reviewed obese children, <8 years of age that underwent polysomnograms (PSG) at SickKids hospital between January 1, 2006 and Dec 31, 2011. The obese cohort was age and sex matched with lean children. Data was collected on demographics, clinical history and PSGs. PSGs were performed in accordance with the American Academy of Sleep Medicine guidelines. We compared 22 obese with 22 lean children. There were 55% males. The mean age ± SD of each of the obese and lean cohorts was 5.12 ± 2.1 years. The mean ± SD BMI for obese and lean children was 31.69 ± 5.20 and 15.73 ± 3.13, p <0.0001. Seventy-three percent (16/22) of each cohort had OSA. The mean ± SD of the obstructive apnea-hypopnea index (AHI) was 22.19 ± 31.22 in obese and 9.52 ±11.6 in lean controls, p=0.082. The mean ± SD oxygen saturation nadir in obese and lean children was 78% ± 18 and 87% ± 9 (p<0.05). The minimum and maximum respiratory rates were higher amongst obese as compared to lean children, p=0.0017 and p=0.0018. In the obese cohort, the obstructive AHI correlated with oxygen saturation nadir (r2=0.74, p<0.0001) and maximum respiratory rate (r2=0.45, p=0.007). Obese children had more severe OSA AHI, lower oxygen saturation nadir and higher respiratory rates than lean children. These data suggest that obese children have increased cardiorespiratory compromise during sleep than their age matched lean peers. Early diagnosis and intervention is paramount to reducing co-morbidity in obese children.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.002 |
| 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 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".