Sleep-Disordered Breathing and Proteinuria in Overweight and Obese Children and Adolescents
Bibliographic record
Abstract
OBJECTIVES: To assess whether sleep-disordered breathing (SDB) in overweight children and adolescents has an additional effect on the spectrum of urinary albumin to protein loss, as markers of early kidney dysfunction. METHODS: Prospective study in a clinical sample of overweight children and adolescents. Each subject underwent anthropometry, blood sampling, oral glucose tolerance test and polysomnography. From a 24-hour urine collection, albumin excretion rate and total urinary protein to creatinine ratio (UPCR) were calculated. RESULTS: 94 nondiabetic subjects were included (mean age = 11.0 +/- 2.5, 42 boys). Average BMI z-score was 2.25 +/- 0.47 (26 overweight subjects and 68 obese subjects). There was no difference in albumin excretion rate or UPCR between subjects with and without SDB. None of the SDB parameters correlated with the transformed albumin excretion rate or UPCR. Albumin excretion rate significantly correlated with fasting insulin and C-peptide and with post-challenge glucose, insulin and C-peptide levels, while UPCR correlated with fasting and post-challenge C-peptide levels. Multiple regression indicated that post-challenge glucose levels were the most important predictors of albumin excretion rate. CONCLUSION: Insulin resistance, and not SDB, was associated with increased levels of albuminuria, indicating early renal dysfunction, in this clinical sample of overweight children and adolescents.
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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 | 0.000 | 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 | 0.000 |
| 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".