Risk of major adverse cardiovascular events and stroke associated with treatment with GLP-1 or the dual GIP/GLP-1 receptor agonist tirzepatide for type 2 diabetes: A systematic review and meta-analysis
Bibliographic record
Abstract
Abstract Introduction: Mounting evidence suggests that glucagon-like-peptide-1 receptor-agonists (GLP-1 RAs) attenuate cardiovascular-risk in type-2 diabetes (T2DM). Tirzepatide is the first-in-class, dual glucose-dependent-insulinotropic-polypeptide GIP/GLP-1 RA approved for T2DM. Patients and methods: A systematic review and meta-analysis of randomized-controlled clinical trials (RCTs) was performed to estimate: (i) the incidence of major adverse cardiovascular events (MACE); and (ii) incidence of stroke, fatal, and nonfatal stroke in T2DM-patients treated with GLP-1 or GIP/GLP-1 RAs (vs placebo). Results: Thirteen RCTs (9 and 4 on GLP-1 RAs and tirzepatide, respectively) comprising 65,878 T2DM patients were included. Compared to placebo, GLP-1RAs or GIP/GLP-1 RAs reduced MACE (OR: 0.87; 95% CI: 0.81–0.94; p < 0.01; I 2 = 37%), all-cause mortality (OR: 0.88; 95% CI: 0.82–0.96; p < 0.01; I 2 = 21%) and cardiovascular-mortality (OR: 0.88; 95% CI: 0.80–0.96; p < 0.01; I 2 = 14%), without differences between GLP-1 versus GIP/GLP-1 RAs. Additionally, GLP-1 RAs reduced the odds of stroke (OR: 0.84; 95% CI: 0.76–0.93; p < 0.01; I 2 = 0%) and nonfatal stroke (OR: 0.85; 95% CI: 0.76–0.94; p < 0.01; I 2 = 0%), whereas no association between fatal stroke and GLP-1RAs was uncovered (OR: 0.80; 95% CI: 0.61–1.05; p = 0.105; I 2 = 0%). In secondary analyses, GLP-1 RAs prevented ischemic stroke (OR: 0.74; 95% CI: 0.61–0.91; p < 0.01; I 2 = 0%) and MACE-recurrence, but not hemorrhagic stroke (OR: 0.92; 95% CI: 0.51–1.66; p = 0.792; I 2 = 0%). There was no association between GLP-1RAs or GIP/GLP-1 RAs and fatal or nonfatal myocardial infarction. Discussion and conclusion: GLP-1 and GIP/GLP-1 RAs reduce cardiovascular-risk and mortality in T2DM. While there is solid evidence that GLP-1 RAs significantly attenuate the risk of ischemic stroke in T2DM, dedicated RCTs are needed to evaluate the efficacy of novel GIP/GLP-1 RAs for primary and secondary stroke prevention.
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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 | 0.009 | 0.019 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.018 | 0.035 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 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".