Atorvastatin 10 mg plus ezetimibe versus titration to atorvastatin 40 mg: attainment of European and Canadian guideline lipid targets in high-risk subjects ≥65 years
Bibliographic record
Abstract
BACKGROUND: Few clinical studies have focused on the efficacy of lipid-lowering therapies in patients ≥65 years. METHODS: After stabilization on atorvastatin 10 mg, hypercholesterolemic subjects ≥65 years at high/very high risk for CHD and not at LDL-C <1.81 mmol/L (with atherosclerotic vascular disease [AVD]) or <2.59 mmol/L (without AVD) were randomized to ezetimibe 10 mg plus atorvastatin 10 mg or uptitration to atorvastatin 20 mg (6 weeks) followed by uptitration to 40 mg (additional 6 weeks). A post-hoc analysis compared between-group differences in percent attainment of individual and combined LDL-C, non-HDL-C and Apo B targets based on recommendations from 2012 European and Canadian Cardiovascular Society (CCS) guidelines for dyslipidemia treatment. RESULTS: Atorvastatin 10 mg plus ezetimibe produced significantly greater attainment of LDL-C, non-HDL-C, and Apo B individual and dual/triple targets vs. atorvastatin 20 mg for the entire cohort and very high-risk groups at 6 weeks. After 12 weeks, very high-risk subjects maintained significantly greater achievement of LDL-C <1.8 mmol/L (47% vs. 35%), non-HDL-C <2.6 mmol/L (63% vs. 53%) and Apo B <0.8 g/L (47% vs. 38%) single targets and dual/triple targets with atorvastatin 10 mg plus ezetimibe vs. atorvastatin 40 mg, while attainment of European target for high-risk subjects was generally similar for both treatments. Achievement of Canadian targets was significantly greater with combination therapy vs. atorvastatin 20 mg (6 weeks) or atorvastatin 40 mg (12 weeks). CONCLUSIONS: Atorvastatin 10 mg plus ezetimibe provided more effective treatment than uptitration to atorvastatin 20/40 mg for attainment of most European and Canadian guideline-recommended lipid targets in older at-risk patients. TRIAL REGISTRATION: ClinicalTrials.gov identifier NCT00418834.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 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 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| 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".