Pantethine, a derivative of vitamin B5, favorably alters total, LDL and non-HDL cholesterol in low to moderate cardiovascular risk subjects eligible for statin therapy: a triple-blinded placebo and diet-controlled investigation
Bibliographic record
Abstract
High serum concentration of low-density lipoprotein cholesterol (LDL-C) is a major risk factor for coronary heart disease. The efficacy of pantethine treatment on cardiovascular risk markers was investigated in a randomized, triple-blinded, placebo-controlled study, in a low to moderate cardiovascular disease (CVD) risk North American population eligible for statin therapy, using the National Cholesterol Education Program (NCEP) guidelines. A total of 32 subjects were randomized to pantethine (600 mg/day from weeks 1 to 8 and 900 mg/day from weeks 9 to 16) or placebo. Compared with placebo, the participants on pantethine showed a significant decrease in total cholesterol at 16 weeks (P=0.040) and LDL-C at 8 and 16 weeks (P=0.020 and P=0.006, respectively), and decreasing trends in non-high-density lipoprotein cholesterol at week 8 and week 12 (P=0.102 and P=0.145, respectively) that reached significance by week 16 (P=0.042). An 11% decrease in LDL-C from baseline was seen in participants on pantethine, at weeks 4, 8, 12, and 16, while participants on placebo showed a 3% increase at week 16. This decrease was significant between groups at weeks 8 (P=0.027) and 16 (P=0.010). The homocysteine levels for both groups did not change significantly from baseline to week 16. Coenzyme Q10 significantly increased from baseline to week 4 and remained elevated until week 16, in both the pantethine and placebo groups. After 16 weeks, the participants on placebo did not show significant improvement in any CVD risk end points. This study confirms that pantethine lowers cardiovascular risk markers in low to moderate CVD risk participants eligible for statins according to NCEP guidelines.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.002 | 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".