Bibliographic record
Abstract
Synchronization of molecular, metabolic, and cardiovascular circadian oscillations is fundamental to human health. Sleep-disordered breathing, which disrupts such temporal congruence, elicits hemodynamic, autonomic, chemical, and inflammatory disturbances with acute and long-term consequences for heart, brain, and circulatory and metabolic function. Sleep apnea afflicts a substantial proportion of adult men and women but is more prevalent in those with established cardiovascular diseases and especially fluid-retaining states. Despite the experimental, epidemiological, observational, and interventional evidence assembled in support of these concepts, this substantial body of work has had relatively modest pragmatic impact, thus far, on the discipline of cardiology. Contemporary estimates of cardiovascular risk still are derived typically from data acquired during wakefulness. The impact of sleep-related breathing disorders rarely is entered into such calculations or integrated into diagnostic disease-specific algorithms or therapeutic recommendations. Reasons for this include absence of apnea-related symptoms in most with cardiovascular disease, impediments to efficient diagnosis at the population level, debate as to target, suboptimal therapies, difficulties mounting large randomized trials of sleep-specific interventions, and the challenging results of those few prospective cardiovascular outcome trials that have been completed and reported. The objectives of this review are to delineate the bidirectional interrelationship between sleep-disordered breathing and cardiovascular disease, consider the findings and implications of observational and randomized trials of treatment, frame the current state of clinical equipoise, identify principal current controversies and potential paths to their resolution, and anticipate future directions.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 0.002 |
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".