High-density lipoprotein cholesterol efflux capacity in patients with obstructive sleep apnea and its relation with disease severity
Bibliographic record
Abstract
Abstract Background Obstructive sleep apnea (OSA) is linked to an accelerated risk of cardiovascular disease (CVD). Some key CVD risk factors are present in patients suffering from OSA such as hypertension, inflammation, oxidative stress, and dyslipidemia. High-density lipoprotein (HDL) cholesterol efflux capacity (CEC) is proposed as a reliable biomarker of HDL function and the present study aimed to quantify this biomarker in patients with OSA. Methods ATP binding cassette subfamily A member 1 (ABCA1), non-ABCA1, and total CEC were determined in 69 polysomnographic-confirmed OSA patients and 23 controls. Moreover, paraoxonase (PON) activities, high-sensitivity C-reactive protein (hsCRP), apolipoprotein B (apo B), and apolipoprotein A-I (apo A-I) circulating levels were quantified in the studied population. Results: All CEC measures were reduced in the OSA group compared to the control group. Strikingly, ABCA1 CEC was diminished in severe OSA in comparison with mild OSA. Furthermore, PON activities and apo A-I showed lower levels, while hsCRP and apo B were elevated in OSA patients compared to controls. Moreover, ABCA1 CEC showed an inverse association with hsCRP and a positive association with apo A-I, while non-ABCA1 CEC presented an association with HDL-C. Conclusion These results suggest the presence of an impaired HDL function in OSA. In particular, ABCA1 CEC was associated with disease severity and inflammation which could be a factor increasing the risk of CVD.
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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 | 0.001 | 0.001 |
| 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) | 0.002 | 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".