Obstructive Sleep Apnea Syndrome: Links Betwen Pathophysiology and Cardiovascular Complications
Bibliographic record
Abstract
PURPOSE: The prevalence of obstructive sleep apnea syndrome (OSAS) is increasing, especially in the middle-aged population. OSAS is associated with an elevated risk of cardiovascular morbidity and mortality. Arterial hypertension is often the first consequence of OSAS, but the most severe complications are coronary artery disease, stroke and arrhythmias. The aim of this review was to analyze the several mechanisms involved in the development of the cardiovascular events, such as endothelial dysfunction accompanied by a pro-inflammatory and pro-oxidant status, hemorheological alterations, hypercoagulability and imbalance between matrix metalloproteases and their inhibitors. SOURCE: A search on PubMed was carried out using the following terms: obstructive sleep apnea syndrome; endothelial dysfunction; oxidative stress; inflammation; rheology; matrix metalloproteases. PRINCIPAL FINDINGS: OSAS severity strongly influenced cardiovascular risk factors and, furthermore, it was correlated with the incidence of fatal and non-fatal events. CONCLUSIONS: The treatment with continuous positive airways pressure (cPAP) is the gold standard for OSAS and was able to positively influence all the pathophysiological mechanisms responsible for cardiovascular diseases. Long-term cPAP improved endothelial function and hemorheology, reduced oxidative stress and inflammation, and decreased the levels of metalloproteases.
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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 | 0.000 | 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 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".