Ezetimibe added to atorvastatin compared with doubling the atorvastatin dose in patients at high risk for coronary heart disease with diabetes mellitus, metabolic syndrome or neither
Bibliographic record
Abstract
AIM: Type 2 diabetes mellitus (T2DM) and metabolic syndrome (MetS) are both associated with increased risk for atherosclerotic coronary heart disease (CHD). Thus, it is useful to know the relative efficacy of lipid-altering drugs in these patient populations. METHODS: A double-blind, parallel group trial of adult patients with hypercholesterolaemia at high-CHD risk receiving atorvastatin 40 mg/day compared atorvastatin 40 mg plus ezetimibe 10 mg (ezetimibe) vs. doubling atorvastatin to 80 mg. This post hoc analysis reports lipid efficacy results in patients grouped by diagnosis of T2DM, MetS without T2DM or neither. Per cent change from baseline at week 6 was assessed for LDL-C, total cholesterol, HDL-C , non-HDL-C , Apo A-I, Apo B and triglycerides. Safety was monitored through clinical and laboratory adverse events (AEs). RESULTS: Compared with doubling atorvastatin, atorvastatin plus ezetimibe resulted in greater reductions in LDL-C, triglycerides, Apo B, non-HDL-C, total cholesterol and lipid ratios in the T2DM, MetS and neither groups. Treatment effects were of similar magnitude across patient groups with both treatments, except triglycerides, which were slightly greater in the T2DM and MetS groups vs. neither group. Changes in HDL-C , Apo A-I and high sensitivity C-reactive protein (hs-CRP) were comparable for both treatments in all three groups. Safety and tolerability profiles were generally similar between treatments and across patient groups, as were the incidence of liver and muscle AEs. CONCLUSIONS: Compared with doubling atorvastatin to 80 mg, addition of ezetimibe to atorvastatin 40 mg produced greater improvements in multiple lipid parameters in high-CHD risk patients with T2DM, MetS or neither, consistent with the significantly greater changes observed in the full study cohort (clinical trial # NCT00276484).
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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 | 0.003 |
| 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 | 0.001 | 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".