Contribution of apo CIII reduction to the greater effect of 12-week micronized fenofibrate than atorvastatin therapy on triglyceride levels and LDL size in dyslipidemic patients
Bibliographic record
Abstract
BACKGROUND: Apolipoprotein (apo) CIII plays an important role in the catabolism of triglyceride-rich lipoproteins as it is a potent inhibitor of lipoprotein lipase (LPL). A low LPL activity has been simultaneously associated with hypertriglyceridemia, low HDL cholesterol and with small LDL particles. AIM: To compare the effects of a 12-week treatment with micronized fenofibrate (200 mg) versus atorvastatin (10 mg) on apo CIII and lipoprotein-lipid levels including LDL size. METHOD: After a 4-week washout period, dyslipidemic patients were randomized to either micronized fenofibrate (n = 64) or atorvastatin (n = 72). RESULTS: Both fenofibrate and atorvastatin significantly decreased apo CIII levels by -0.03 +/- 0.03 versus -0.01 +/- 0.03 g/l respectively, and increased LDL size by 4.9 +/- 3.3 versus 1.8 +/- 2.9 A. Improvements in these parameters were significantly greater with fenofibrate (P < 0.0001). Significant relationships were found between changes in triglycerides and changes in apo CIII (r = 0.81 and r = 0.59, P < 0.0001) as well as between changes in LDL size and changes in apo CIII (r = -0.41 and r = -0.45, P < 0.001), in both fenofibrate and atorvastatin groups. respectively. CONCLUSION: The substantial reduction in apo CIII induced by micronized fenofibrate plays an important role in the greater effect of micronized fenofibrate than atorvastatin on plasma triglycerides and LDL size.
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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) | 0.002 | 0.001 |
| 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 | 0.001 |
| 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".