Cardiovascular consequences of obstructive sleep apnea
Bibliographic record
Abstract
PURPOSE OF REVIEW: There is an increased awareness of obstructive sleep apnea (OSA) and its potential impact on cardiovascular diseases (CVDs). The number of patients diagnosed with OSA is likely to increase as the obesity epidemic continues to grow. We review recent publications that have examined the links between OSA and CVD. RECENT FINDINGS: The cardiovascular consequences of OSA include hypertension, strokes, atrial fibrillation, and heart failure. It is likely that these are related to OSA-induced changes in endothelial dysfunction, oxidative stress, and systemic inflammation. The mainstay of treatment of OSA remains positive airway pressure devices (PAP), but issues of adherence continue to plague effective management. Oral appliances may also be a suitable alternative and may have a similar effect on blood pressure as PAP. To date, randomized trials have verified a significant (though relatively modest) impact of PAP on blood pressure, and some have shown an improvement in glucose control in diabetic individuals. However, it is unclear whether PAP prevents cardiovascular events in patients with OSA, although patients well managed and adherent with PAP seem to do better than those who are nonadherent. SUMMARY: The mortality and morbidity associated with OSA are reduced in patients well managed with PAP. However, we await the results of large randomized clinical trials to definitely determine whether PAP reduces the rate of cardiovascular events. Current efforts aimed at identifying biomarkers in OSA may offer a strategy for personalized treatment plans of OSA patients.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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".