Effects of albiglutide on myocardial infarction and ischaemic heart disease outcomes in patients with type 2 diabetes and cardiovascular disease in the Harmony Outcomes trial
Bibliographic record
Abstract
AIMS: Large outcome trials have demonstrated cardiovascular benefits of selected glucagon-like peptide-1 (GLP-1) receptor agonists. We examined coronary disease outcomes in the Harmony Outcomes trial of the GLP-1 receptor agonist albiglutide. METHODS AND RESULTS: Harmony Outcomes was an event-driven, multicenter, double-blind, and placebo-controlled trial involving 9463 patients >40 years of age with type-2 diabetes and established atherosclerotic cardiovascular disease. It tested the effects of albiglutide on the occurrence of a composite primary endpoint, consisting of cardiovascular death, myocardial infarction (MI), or stroke. Within this post-hoc analysis, the effects of albiglutide on MI subtypes and other ischaemic endpoints were analysed.During the median-follow up of 1.6 years, a total of 421 patients (4.5%) experienced at least one MI, with 72 patients having more than one event. Treatment with albiglutide reduced both first events [hazard ratio (HR) 0.75 (0.62-0.91)] and overall events [HR 0.75 (0.61-0.91)] as well as first type 1 [HR 0.73 (0.57-0.92)] and type 2 myocardial infarctions [HR 0.65 (0.46-0.92)]. The effect of albiglutide treatment was consistent for ST-segment elevation [HR 0.69 (0.38-1.26)] and non-ST elevation (HR 0.86 (0.66-1.2) MI. CONCLUSION: Treatment with the GLP-1 receptor agonist albiglutide resulted in a 25% relative risk reduction in MI that was consistent for type of infarction and presence or absence of ST elevation. Our findings add novel information about the effects of GLP-1 receptor agonists on ischaemic events in patients with type 2 diabetes.
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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 | 0.003 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".