Obstructive sleep apnoea is associated with diabetes in sleepy subjects
Bibliographic record
Abstract
BACKGROUND: Although obstructive sleep apnoea (OSA) has been linked to insulin resistance and glucose intolerance, it is unclear whether there is an independent association between OSA and diabetes mellitus (DM) and whether all patients with OSA are at risk. The objective of this study was to determine the association between OSA and DM in a large cohort of patients referred for sleep diagnostic testing. METHODS: A cross-sectional analysis of participants in a clinic-based study was conducted between July 2005 and August 2007. DM was defined by self-report and concurrent use of diabetic medications (oral hypoglycaemics and/or insulin). Sensitivity analysis was performed using a validated administrative definition of diabetes. OSA was defined by the respiratory disturbance index (RDI) using polysomnography or ambulatory monitoring. Severe OSA was defined as an RDI > or = 30/h. Subjective sleepiness was defined as an Epworth Sleepiness Scale score > or = 10. RESULTS: Complete data were available for 2149 patients. The prevalence of DM increased with increasing OSA severity (p<0.001). Severe OSA was associated with DM following adjustment for patient demographics, weight and neck circumference (odds ratio (OR) 2.18; 95% CI 1.22 to 3.89; p<0.01). Following a stratified analysis, this relationship was observed exclusively in sleepy patients (OR 2.59 (95% CI 1.35 to 4.97) vs 1.16 (95% CI 0.31 to 4.37) in non-sleepy patients). CONCLUSIONS: Severe OSA is independently associated with DM in patients who report excessive sleepiness. Future studies investigating the impact of OSA treatment on DM may wish to focus on this patient population.
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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".