Chronic Kidney Disease and Sleep Apnea Association of Kidney Disease With Obstructive Sleep Apnea in a Population Study of Men
Bibliographic record
Abstract
Study Objectives: To determine the relationship between obstructive sleep apnea (OSA) and chronic kidney disease (CKD). Previous population studies of the association are sparse, conflicting and confined largely to studies of administrative data. Methods: Cross-sectional analysis in unselected participants of the Men Androgens Inflammation Lifestyle Environment and Stress (MAILES) study, aged >40 years. Renal data were available for 812 men without a prior OSA diagnosis who underwent full in-home polysomnography (Embletta X100) in 2010-2011. CKD was defined as an estimated glomerular filtration rate (eGFR) <60 mL/min/1.73m2 or eGFR≥60 and albuminuria (albumin-creatinine ratio ≥3.0 mg/mmol). Results: CKD (10.5%, n = 85 [Stage 1-3, 9.7%; Stage 4-5, 0.7%]) of predominantly mild severity showed significant associations with OSA (apnea-hypoapnea index [AHI] ≥ 10): odds ratio (OR) = 1.9, 95% confidence interval (CI): 1.02-3.5; severe OSA (AHI ≥ 30/h): OR = 2.6, 95% CI: 1.1-6.2; and respiratory-related arousal index: ≥7.6/h, OR = 2.3, 95%CI: 1.1-4.7; but not measures of hypoxemia after adjustment for age, hypertension, diabetes, smoking, obesity, and NSAID use. There was no association of CKD with daytime sleepiness. In men with CKD, those with OSA were not significantly more likely to report symptoms (sleepiness, snoring, and apneas) or be identified with the STOP OSA screening questionnaire, compared to men without OSA. Conclusions: Predominantly mild CKD is associated with severe OSA and arousals. Further population studies examining the longitudinal relationship between CKD and OSA are warranted. Better methods are needed to identify OSA in CKD which may have few symptoms.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".