P2858Liraglutide reduces cardiovascular events and mortality in type 2 diabetes independent of LDL cholesterol and statin use: results of the LEADER trial
Bibliographic record
Abstract
Background: The relationships among low-density lipid cholesterol (LDL-C) levels, statin use and cardiovascular (CV) outcomes are well established. In the LEADER trial, the human glucagon-like peptide 1 analogue liraglutide reduced CV events in patients with type 2 diabetes (T2D) at high CV risk. Purpose: This post hoc analysis evaluated liraglutide effects on CV outcomes by baseline LDL-C and statin use. Methods: LEADER (NCT01179048) studied liraglutide (1.8 mg or maximum tolerated dose) vs placebo, both in addition to standard care, in 9340 patients with T2D and high CV risk (median follow-up 3.8 years). Primary outcome: composite of CV death, non-fatal myocardial infarction, or non-fatal stroke (major adverse CV events, MACE). The key secondary expanded outcome (expanded MACE) also included hospitalisation for unstable angina or heart failure, or revascularisation. Cox regression evaluated the liraglutide effect on CV outcomes by baseline LDL-C <1.3 mmol/L, 1.3–1.8 mmol/L and >1.8 mmol/L, and statin use at baseline.
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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 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".