Obstructive Sleep Apnea Increases Sudden Cardiac Death in Incident Hemodialysis Patients
Bibliographic record
Abstract
BACKGROUND: Mortality in end-stage renal disease (ESRD) occurs predominantly from cardiovascular disease (CVD) and sudden cardiac death (SCD). Obstructive sleep apnea (OSA) is characterized by periodic airflow limitation associated with sleep arousal and oxygen desaturation and is prevalent in patients with ESRD. Whether OSA increases the risk for SCD, cardiovascular and all-cause mortality among hemodialysis patients remains unknown. METHODS: In a prospective cohort of 558 incident hemodialysis patients, we examined the association of OSA with all-cause mortality, cardiovascular mortality, and SCD using Cox proportional hazards models controlling for traditional CVD risk factors. RESULTS: Sixty-six incident hemodialysis patients (12%) had OSA. Mean age (56 years) and percentage of males (56%) were identical in OSA and no-OSA groups. Fewer African Americans had OSA than non-African Americans (9 vs. 18%, respectively). Participants with OSA had higher body-mass index, Charlson comorbidity score, and left ventricular mass index and greater prevalence of diabetes and coronary artery disease. During 1,080 person-years of follow-up, 104 deaths occurred, 29% of which were cardiovascular. OSA was associated with a higher risk of all-cause mortality (HR 1.90 [95% CI 1.04-3.46]) and cardiovascular mortality (HR 3.62 [95% CI 1.36-9.66]) after adjusting for demographics and body-mass index. OSA was associated with a higher risk of SCD after adjusting for demographics (HR 3.28 [95% CI 1.12-9.57]) and multiple cardiovascular risk factors. CONCLUSIONS: Incident hemodialysis patients with OSA are at increased risk of all-cause and cardiovascular mortality and SCD. Future studies should assess the impact of screening for OSA and OSA-targeted interventions on mortality in ESRD.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".