Differential effects of glucagon-like peptide-1 receptor agonist classes on blood pressure: a systematic review and network meta-analysis of randomised controlled trials with meta-regression
Bibliographic record
Abstract
Background and Aims: Recent clinical trials have reported blood pressure (BP)-lowering effects of glucagon-like peptide-1 receptor agonists (GLP1Ra). A recent systematic review has focused on the effects of semaglutide. However, there has been no comprehensive evaluation of the BP effects of all GLP1Ra available, including the double agonist tirzepatide and the triple agonist retatrutide. Additionally, the extent to which BP reduction is mediated by weight loss remains unclear. This systematic review and network meta-analysis aimed to evaluate the impact of GLP1Ra on systolic and diastolic BP across randomized controlled trials (RCTs). Methods: PubMed/MEDLINE, Web of Science and Ovid/Embase were searched from their inception until 31st July 2024. RCTs involving adult patients treated with GLP1Ra that reported BP and weight changes were included. Pair-wise meta-analysis and meta-regression models were utilised. Network meta-analysis was conducted. Mean difference (MD) and its 95% confidence intervals (CIs) were reported. Results: A total of 75 RCTs, including 114352 participants, were included. Retatrutide demonstrated the greatest reduction in systolic BP (MD: −7.0 mmHg; 95% CI: −10.5 to −3.5, followed by tirzepatide (MD: −5.2 mmHg; 95% CI: −6.9 to −3.5) and semaglutide (MD: −3.4 mmHg; 95% CI: −4.7 to −2.1). For diastolic BP, tirzepatide showed the largest reduction (MD: −1.7 mmHg; 95% CI: −2.6 to −0.8), followed by semaglutide (MD: −0.8 mmHg; 95% CI: −1.4 to −0.2). Mediation analysis indicated that weight loss partially mediated the BP-lowering effects of GLP1Ra. Conclusion: Retatrutide, tirzepatide and semaglutide reduced systolic blood pressure compared to placebo. Tirzepatide and semaglutide also led to significant diastolic BP reductions. The triple agonist retatrutide emerged as the most effective agent for lowering systolic BP among all GLP1Ra classes.
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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 | 0.027 | 0.057 |
| Meta-epidemiology (narrow) | 0.004 | 0.002 |
| Meta-epidemiology (broad) | 0.027 | 0.065 |
| Bibliometrics | 0.009 | 0.010 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".