Semaglutide and blood pressure: an individual patient data meta-analysis
Bibliographic record
Abstract
BACKGROUND AND AIMS: Randomized clinical trials (RCTs) assessing semaglutide reported reductions of systolic blood pressure (SBP) in trial populations with baseline blood pressure in the normotensive range. This study aimed to determine whether this SBP reduction is greater in hypertensive groups. METHODS: Individual patient data (IPD) from three RCTs examining the effect of semaglutide 2.4 mg on body weight over 68 weeks were included. Trial participants were categorized according to a hypertension diagnosis, treatment or baseline measurement (HTN), baseline SBP > 130 mmHg (HTN130) or >140 mmHg (HTN140), and those with apparent resistant hypertension (RH). The primary analysis compared the in-trial change in SBP in the semaglutide and placebo arms. Alterations of anti-hypertensive medications were quantified by treatment intensity score and compared between arms. These analyses were performed using analysis of covariance. RESULTS: Overall, 3136 participants were included. The difference in SBP change between the treatment (n = 2109) and placebo (n = 1027) groups was -4.95 mmHg [95% confidence interval (CI) -5.86 to -4.05] overall. This difference was -4.78 mmHg (95% CI -5.97 to -3.59) for HTN, -4.93 mmHg (95% CI -6.75 to -3.11) for HTN130, -4.09 mmHg (95% CI -7.12 to -1.06) for HTN140, and -3.16 mmHg (95% CI -8.69-2.37) for RH. Reduction in SBP was mediated substantially by weight loss. The anti-hypertensive treatment intensity score decreased for those on semaglutide compared to placebo (-0.51; 95% CI -0.71 to -0.32). CONCLUSIONS: This IPD analysis of three large RCTs found blood pressure reductions with semaglutide in participants with hypertension that were similar to those seen in all trial participants. This finding may in part be due to concurrent reductions to anti-hypertensive medications. These results suggest that semaglutide is a useful adjunctive treatment for patients with hypertension and obesity.
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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 | 0.025 | 0.037 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.015 | 0.052 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 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".