Minimal contribution of nausea or vomiting to superior semaglutide-mediated weight loss vs. exenatide and dulaglutide in type 2 diabetes
Bibliographic record
Abstract
Background: Semaglutide showed superior HbA1c and body weight reductions vs. comparators in SUSTAIN clinical trials. A analysis showed the contribution of nausea or vomiting to superior body weight loss with semaglutide in SUSTAIN 1 – 5 was small. This post hoc analysis assessed the contribution of nausea or vomiting to the greater weight loss with semaglutide vs. exenatide extended-release (ER) and dulaglutide. Materials: Subjects with T2D were randomised to semaglutide 1.0 mg vs. exenatide ER 2.0 mg in SUSTAIN 3 or semaglutide 1.0 mg vs. dulaglutide 1.5 mg and semaglutide 0.5 mg vs. dulaglutide 0.75 mg in SUSTAIN 7. A mediation analysis was done to determine how much of the estimated treatment differences in weight loss was due to direct effects of semaglutide vs. nausea or vomiting. Results: In SUSTAIN 3, proportions of subjects experiencing nausea or vomiting were 24.0 (semaglutide) vs. 14.1% (exenatide ER). In SUSTAIN 7, 24.0 vs. 23.1% (semaglutide 1.0 mg vs. dulaglutide 1.5 mg). In SUSTAIN 7, mean changes in body weight from baseline were -7.6 vs. -3.9 kg (semaglutide 1.0 mg vs. dulaglutide 1.5 mg) in those with nausea or vomiting, and -6.2 vs. -2.7 kg (semaglutide 1.0 mg vs. dulaglutide 1.5 mg) in those without. Conclusion: In SUSTAIN 3 and 7, body weight reductions were significantly greater with semaglutide vs. exenatide ER and dulaglutide in subjects with and without nausea or vomiting. Nausea or vomiting contributed minimally to the superior weight reductions.
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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 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".