Effects of the Once-Weekly Glucagon-Like Peptide-1 Receptor Agonist Dulaglutide on Ambulatory Blood Pressure and Heart Rate in Patients With Type 2 Diabetes Mellitus
Bibliographic record
Abstract
Glucagon-like peptide-1 receptor agonists, used to treat type 2 diabetes mellitus, are associated with small reductions in systolic blood pressure (SBP) and increases in heart rate. However, findings based on clinic measurements do not adequately assess a drug's 24-hour pharmacodynamic profile. The effects of dulaglutide, a once-weekly glucagon-like peptide-1 receptor agonist, on BP and heart rate were investigated using ambulatory BP monitoring. Patients (n=755; 56±10 years; 81% white; 48% women), with type 2 diabetes mellitus, taking ≥1 oral antihyperglycemic medication, with a clinic BP between 90/60 and 140/90 mm Hg were randomized to dulaglutide (1.5 or 0.75 mg) or placebo subcutaneously for 26 weeks. Ambulatory BP monitoring was performed at baseline and at 4, 16, and 26 weeks. The primary end point was change from baseline to week 16 in mean 24-hour SBP, a tree gatekeeping strategy compared the effects of dulaglutide to placebo. Both doses of dulaglutide were noninferior to placebo for changes in 24-hour SBP and diastolic blood pressure, and dulaglutide 1.5 mg significantly reduced SBP (least squares mean difference [95% confidence interval]), -2.8 mm Hg [-4.6, -1.0]; P≤0.001). Dulaglutide 0.75 mg was noninferior to placebo (1.6 bpm; [0.3, 2.9]; P≤0.02) for 24-hour heart rate (least squares mean difference [95% confidence interval]), but dulaglutide 1.5 mg was not (2.8 bpm [1.5, 4.2]). Dulaglutide 1.5 mg was associated with a reduction in 24-hour SBP and an increase in 24-hour heart rate. The mechanisms responsible for the observed effects remain to be clarified.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".