Effect of obstructive sleep apnea on carotid artery intima media thickness related to inflammation
Bibliographic record
Abstract
PURPOSE: Obstructive sleep apnea hypopnea syndrome (OSAHS) is an independent risk factor for atherosclerosis. To ascertain the effect of OSAHS on the development of atherosclerosis in Chinese OSAHS patients, we evaluated markers of atherosclerosis as well as vascular endothelial function and inflammation. METHODS: Chinese men with polysomnography-diagnosed OSAHS were subgrouped into mild-moderate (n = 28) and severe (n = 54) OSAHS groups on the basis of apnea hypopnea index (AHI) scores. The control group was made up of 30 healthy men. Atherosclerosis was assessed by carotid artery intima-media thickness (IMT) of both sides, flow-mediated dilation (FMD), and inflammation by interleukin-6 (IL-6), high-sensitivity C-reactive protein (hs-CRP), vascular endothelial growth factor (VEGF), and monocyte chemoattractant protein-1 (MCP-1) levels. RESULTS: Linear regression analysis was used to identify significant associations among risk factors and carotid IMT. The following parameters were significantly higher in patients with severe OSAHS than in the control group: waking triglycerides, total cholesterol, low-density lipoprotein cholesterol, apolipoprotein B, blood uric acid, blood glucose, IL-6 and hs-CRP. FMD in severe OSAHS patients was lower than in the control group. AHI score, waking hs-CRP, waking oxidized low-density lipoprotein, blood glucose, and vascular endothelial growth factor (VEGF) level were positively associated with IMT. CONCLUSIONS: In Chinese male patients with severe OSAHS, the significantly higher carotid IMT and levels of inflammatory factors (IL-6 and hs-CRP) and lower FMD suggest that arterial endothelial damage and inflammation may play important roles in the development of atherosclerosis in OSAHS 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 | 0.000 | 0.001 |
| 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) | 0.001 | 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".