Comparison of tirzepatide and dulaglutide on major adverse cardiovascular events in participants with type 2 diabetes and atherosclerotic cardiovascular disease: SURPASS‐CVOT design and baseline characteristics
Bibliographic record
Abstract
Tirzepatide, a once weekly GIP/GLP-1 receptor agonist, reduces blood glucose and body weight in people with type 2 diabetes. The cardiovascular (CV) safety and efficacy of tirzepatide have not been definitively assessed in a cardiovascular outcomes trial. Tirzepatide is being studied in a randomized, double-blind, active-controlled CV outcomes trial. People with type 2 diabetes aged ≥40 years, with established atherosclerotic CV disease, HbA1c ≥7% to ≤10.5%, and body mass index ≥25 kg/m2 were randomized 1:1 to once weekly subcutaneous injection of either tirzepatide up to 15 mg or dulaglutide 1.5 mg. The primary outcome is time to first occurrence of any major adverse cardiovascular event (MACE), defined as CV death, myocardial infarction, or stroke. The trial is event-driven and planned to continue until ≥1,615 participants experience an adjudication-confirmed component of MACE. The primary analysis is non-inferiority for time to first MACE of tirzepatide versus dulaglutide by demonstrating an upper confidence limit <1.05, which will also confirm superiority versus a putative placebo, and also to determine whether tirzepatide produces a greater CV benefit than dulaglutide (superiority analysis). Over 2 years, 13,299 people at 640 sites in 30 countries across all world regions were randomized. The mean age of randomized participants at baseline was 64.1 years, diabetes duration 14.7 years, HbA1c 8.4%, and BMI 32.6 kg/m2. Overall, 65.0% had coronary disease, of whom 47.3% reported prior myocardial infarction and 57.4% had prior coronary revascularization. 19.1% of participants had prior stroke and 25.3% had peripheral artery disease. The trial is fully recruited and ongoing. SURPASS-CVOT will provide definitive evidence as to the CV safety and efficacy of tirzepatide as compared with dulaglutide, a GLP-1 receptor agonist with established CV benefit.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.004 |
| 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 | 0.001 |
| 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".