Efficacy of Statin Monotherapy or in Combination With Coenzyme A Capsule in Patients With Metabolic Syndrome and Mixed Dyslipidemia
Bibliographic record
Abstract
BACKGROUND: Patients with metabolic syndrome are at increased risk for cardiovascular disease. Combination lipid-lowering therapy is often needed in patients with metabolic syndrome and mixed dyslipidemia. The aim of this study was to compare the effect of statin combined with a new hypolipidemic agent, coenzyme A (CoA) with moderate-dose statin monotherapy in subjects with metabolic syndrome and mixed dyslipidemia by evaluating data from a subgroup of patients with metabolic syndrome and mixed dyslipidemia from a previously conducted randomized study. METHODS: In the present post hoc analysis, 212 patients were included, receiving statin monotherapy (n = 94) or statin combined with CoA 400 U/day (n = 118) for 8 weeks. The lipoprotein profile was determined at baseline and week 8 visits. Attainment of low-density lipoprotein-cholesterol (LDL-C) < 100 mg/dL, non-high-density lipoprotein-cholesterol (HDL-C) < 130 mg/dL, and the combined goal of these two parameters was also evaluated. RESULTS: The mean percent change was more prominent with CoA plus statin compared with placebo plus statin in triglyceride (TG) (-32.5% vs. -8.7%, respectively; P = 0.0002), total cholesterol (-9.6% vs. -3.6%, P = 0.013), LDL-C (-7.5% vs. 2.1%, P = 0.033), and non-HDL-C (-14.3% vs. -6.4%, P = 0.011). Treatment with CoA plus statin resulted in larger percentages of participants attaining lipid goals for LDL-C (70.3% vs. 56.4%, P = 0.044), non-HDL-C (60.2% vs. 45.7%, P = 0.039), and the combined goal of LDL-C and non-HDL-C (57.6% vs. 42.6%, P = 0.038) than statin monotherapy. CONCLUSION: These results demonstrate that CoA plus statin therapy was more effective in improving lipoprotein parameters than statin alone in patients with metabolic syndrome and mixed hyperlipidemia.
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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 | 0.006 | 0.020 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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".