Effect of albiglutide on cardiovascular outcomes in older adults: A post hoc analysis of a randomized controlled trial
Bibliographic record
Abstract
AIM: To analyse the effects of albiglutide, a glucagon-like peptide 1 receptor agonist, on cardiovascular outcomes in older adults aged ≥65 years with type 2 diabetes and cardiovascular disease who participated in the Harmony Outcomes trial (NCT02465515). MATERIALS AND METHODS: We conducted a post hoc analysis of the primary endpoint of the Harmony Outcomes trial-time to first occurrence of a major adverse cardiovascular event-in subgroups of participants aged <65 and ≥65 years and <75 and ≥75 years at baseline. Hazard ratios and 95% confidence intervals (CIs) were generated using Cox proportional hazards regression. RESULTS: The analysis population included 9462 Harmony Outcomes participants, including 4748 patients ≥65 and 1140 patients ≥75 years at baseline. Hazard ratios for the prevention of major adverse cardiovascular events were 0.66 (95% CI, 0.53-0.82) in persons <65 and 0.86 (95% CI, 0.71-1.04) in those ≥65 years (age interaction p = .07), and 0.78 (95% CI, 0.67-0.91) in <75 and 0.70 (95% CI, 0.48-1.01) in ≥75 year age groups (interaction p = .6). When analysed as a continuous variable, age did not modify the effect of albiglutide on the primary endpoint. CONCLUSIONS: This post hoc analysis adds to the body of literature showing that glucagon-like peptide 1 receptor agonists added to standard type 2 diabetes therapy safely reduce the incidence of cardiovascular events in older adults with established cardiovascular disease. In this analysis, the risk-benefit profile was similar between younger and older age groups treated with albiglutide.
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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 | 0.018 | 0.020 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.009 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 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".