Cardiovascular Disease and Health-Care Utilization in Snorers: a Population Survey
Bibliographic record
Abstract
STUDY OBJECTIVES: We assessed the prevalence of self-reported snoring in the Hungarian population and established whether different types of snoring are associated with cardiovascular disorders and increased health-care utilization. DESIGN: Cross-sectional study. Door-to-door survey. SETTING: Nationally representative population in Hungary. PARTICIPANTS: Interviews were carried out in the homes of 12,643 persons. We used the Hungarian National Population Register as the sampling frame and implemented a clustered, stratified sampling procedure. The study population represented 0.16% of the population over the age of 18 years according to age, sex, and 150 subregions of the country. INTERVENTIONS: Not applicable. MEASUREMENTS AND RESULTS: Thirty-seven percent of men and 21% of women reported loud snoring with breathing pauses. Hypertension, myocardial infarction, and stroke were reported by 26%, 3%, and 4% of the respondents, respectively. There was a significant increase in the prevalence of hypertension, myocardial infarction, and stroke in quiet and loud snorers, as compared with nonsnorers. Multivariate analysis showed an association between loud snoring and hypertension (odds ratio [OR]: 1.40, 95% confidence interval [CI]: 1.24-1.58), myocardial infarction (OR: 1.34, CI: 1.04-1.73), and stroke (OR: 1.67, CI: 1.32-2.11) after statistical adjustment for age, sex, body mass index, diabetes, level of education, smoking, and alcohol consumption. Loud snoring was also associated with measures of health-care use in both sexes. CONCLUSIONS: Snoring is frequent in the Hungarian adult population, and loud snoring with breathing pauses, in contrast with quiet snoring, is associated with an increased risk of cardiovascular disease and increased health-care utilization.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.000 | 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 teacher head, 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".