Fibrinogen may mediate the association between long sleep duration and coronary heart disease
Bibliographic record
Abstract
Long sleep duration has been associated with increased risk of cardiovascular disease (CVD) and all-cause mortality. Inflammation and coagulation have been hypothesized as possible physiological pathways to explain this association, although specific biomarkers have not been studied. Using longitudinal data from 3942 postmenopausal women in the Women's Health Initiative observational study and clinical trials, we investigated whether fibrinogen, an acute-phase inflammatory protein involved in blood clotting, mediates the associations between sleep duration and coronary heart disease (CHD) and mortality among women. Fibrinogen levels were associated positively with self-reported long sleep duration (9+ h per night), CHD and all-cause mortality, even after adjustment for a range of sociodemographic characteristics, cardiovascular risk factors and comorbidities.Compared with self-reported 7-8 h per night sleep duration, self-reported long sleep duration was associated with increased odds of CHD [odds ratio (OR) = 2.05, 95% confidence interval (CI): 1.02-4.11]. Adjustment for fibrinogen levels reduced the increased odds of CHD associated with long sleep by approximately 8 percentage points (OR = 1.97, 95% CI: 0.98-3.97). A similar reduction in the OR was observed with mortality. For both outcomes there is support for partial mediation of 6-7%, suggesting that fibrinogen may be a mechanism through which long sleep duration is associated with CHD and mortality.
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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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".