Efficacy of ezetimibe/simvastatin 10/20 and 10/40 mg compared with atorvastatin 20 mg in patients with type 2 diabetes mellitus*
Bibliographic record
Abstract
AIM: This randomized, double-blind study evaluated the efficacy of switching from atorvastatin (ATV) 10 mg to ezetimibe/simvastatin (EZE/SIMVA) 10/20 mg, EZE/SIMVA 10/40 mg or doubling the dose of ATV from 10 to 20 mg in patients with type 2 diabetes (T2D). METHODS: Eligible patients had haemoglobin A(1C)< or =10%, were aged > or =18 years and were on ATV 10 mg for > or =6 weeks before study entry. After a 4-week open-label ATV 10 mg run-in, patients were randomized to EZE/SIMVA 10/20 mg (n = 220), EZE/SIMVA 10/40 mg (n = 222) or ATV 20 g (n = 219) daily for 6 weeks. RESULTS: Greater (p < or = 0.001) reductions in low-density lipoprotein cholesterol (LDL-C) (the primary end-point) were achieved by switching to EZE/SIMVA 10/20 mg (26.2%) or 10/40 mg (30.1%) than by doubling the dose of ATV to 20 mg (8.5%). EZE/SIMVA 10/20 mg and 10/40 mg produced greater (p < or = 0.001) reductions in total cholesterol, non-high-density lipoprotein cholesterol (HDL-C) and apolipoprotein B relative to ATV 20 mg. A reduction (p < or = 0.050) in C-reactive protein was observed with EZE/SIMVA 10/40 mg vs. ATV 20 mg. Similar reductions in triglycerides were observed across the three groups, and none of the treatments produced a significant change in HDL-C. A greater (p < or = 0.001) proportion of patients achieved LDL-C <2.5 mmol/l with EZE/SIMVA 10/20 mg (90.5%) and 10/40 mg (87.0%) than with ATV 20 mg (70.4%). Both EZE/SIMVA doses were generally well tolerated, with an overall safety profile similar to ATV 20 mg. CONCLUSIONS: EZE/SIMVA 10/20 and 10/40 mg provided greater lipid-altering efficacy than doubling the dose of ATV from 10 to 20 mg and were well tolerated in patients with T2D.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| 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 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".