Longitudinal Changes in Cholesterol Efflux Capacities in Patients With Coronary Artery Disease Undergoing Lifestyle Modification Therapy
Bibliographic record
Abstract
Background Our objective was to identify the determinants of high‐density lipoprotein cholesterol efflux capacity ( HDL ‐ CEC ) changes in patients with coronary artery disease who participated in a lifestyle modification program aimed at increasing physical activity levels and improving diet quality. Methods and Results A total of 86 men with coronary artery disease aged between 35 and 80 years participated in a 1‐year lifestyle modification program that aimed to achieve a minimum of 150 minutes of aerobic physical activity weekly and improve diet quality. HDL ‐ CEC s were measured before and after the 1‐year intervention using 3 H‐cholesterol–labeled J774 and HepG2 cells. Visceral, subcutaneous, and cardiac adipose tissue levels were assessed before and after the intervention using magnetic resonance imaging. Lipoprotein particle size and concentrations were measured by proton nuclear magnetic resonance spectroscopy and a complete lipoprotein‐lipid profile was obtained. At baseline, the best correlate of HDL ‐ CEC s were apolipoprotein AI ( R 2 =0.35, P <0.0001) and high‐density lipoprotein cholesterol ( R 2 =0.21, P <0.0001) for J774‐ HDL ‐ CEC s and HepG2‐ HDL ‐ CEC s, respectively. Baseline and longitudinal changes in HDL ‐ CEC s were associated with several lipoprotein size and concentration indices, although high‐density lipoprotein cholesterol was the best predictor of longitudinal changes in J774‐ HDL ‐ CEC s ( R 2 =0.18, P =0.002) and apolipoprotein AI was found to be the best predictor of longitudinal changes in HepG2 cholesterol efflux capacities ( R 2 =0.21, P =0.002). Conclusions Results of this study suggest that increases in high‐density lipoprotein cholesterol and apolipoprotein AI levels typically observed in patients with coronary artery disease undergoing healthy lifestyle modification therapy may be indicative of higher plasma concentrations of functional high‐density lipoprotein particles.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| 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) | 0.000 | 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 teacher head, 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".