Association of incident obstructive sleep apnoea with outcomes in a large cohort of US veterans
Bibliographic record
Abstract
RATIONALE: There is a paucity of large cohort studies examining the association of obstructive sleep apnoea (OSA) with clinical outcomes including all-cause mortality, coronary heart disease (CHD), strokes and chronic kidney disease (CKD). OBJECTIVES: We hypothesised that a diagnosis of incident OSA is associated with higher risks of these adverse clinical outcomes. METHODS, MEASUREMENTS: In a nationally representative cohort of over 3 million (n=3 079 514) US veterans (93% male) with baseline estimated glomerular filtration rate (eGFR)≥60 mL/min/1.73 m(2), we examined the association between the diagnosis of incident OSA, treated and untreated with CPAP, and: (1) all-cause mortality, (2) incident CHD, (3) incident strokes, (4)incident CKD defined as eGFR<60 mL/min/1.73 m(2), and (5) slopes of eGFR. MAIN RESULTS: Compared with OSA-negative patients, untreated and treated OSA was associated with 86% higher mortality risk, (adjusted HR and 95% CI 1.86 (1.81 to 1.91) and 35% (1.35 (1.21 to 1.51)), respectively. Similarly, untreated and treated OSA was associated with 3.5 times (3.54 (3.40 to 3.69)) and 3 times (3.06 (2.62 to 3.56)) higher risk of incident CHD; 3.5 times higher risk of incident strokes (3.48 (3.28 to 3.64) and 3.50 (2.92 to 4.19)) for untreated and treated OSA, respectively. The risk of incident CKD was also significantly higher in untreated (2.27 (2.19 to 2.36)) and treated (2.79 (2.48 to 3.13)) patients with OSA. The median (IQR) of the eGFR slope was -0.41 (-2.01 to 0.99), -0.61 (-2.69 to 0.93) and -0.87 (-3.00 to 0.70) mL/min/1.73 m(2) in OSA-negative patients, untreated OSA-positive patients and treated OSA-positive patients, respectively. CONCLUSIONS: In this large and contemporary cohort of more than 3 million US veterans, a diagnosis of incident OSA was associated with higher mortality, incident CHD, stroke and CKD and with faster kidney function decline.
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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 | 0.002 | 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 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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".