Semaglutide induces weight loss in subjects with type 2 diabetes regardless of baseline <scp>BMI</scp> or gastrointestinal adverse events in the SUSTAIN 1 to 5 trials
Bibliographic record
Abstract
AIMS: To assess the effect of baseline body mass index (BMI) and the occurrence of nausea and/or vomiting on weight loss induced by semalgutide, a once-weekly glucagon-like peptide 1 analogue for the treatment of type 2 diabetes. Semaglutide demonstrated superior reductions in HbA1c and superior weight loss (by 2.3-6.3 kg) versus different comparators across the SUSTAIN 1 to 5 trials; the contributing factors to weight loss are not established. MATERIALS AND METHODS: Subjects with inadequately controlled type 2 diabetes (drug-naïve or on background treatment) were randomized to subcutaneous semaglutide 0.5 mg (excluding SUSTAIN 3), 1.0 mg (all trials), or comparator (placebo, sitagliptin, exenatide extended release or insulin glargine). Subjects were subdivided by baseline BMI and reporting (yes/no) of any nausea and/or vomiting. Change from baseline in body weight was assessed within each trial and subgroup. A mediation analysis separated weight loss into direct or indirect (mediated by nausea or vomiting) effects. RESULTS: Clinically relevant weight-loss differences were observed across all BMI subgroups, with a trend towards higher absolute weight loss with higher baseline BMI. Overall, 15.2% to 24.0% and 21.5% to 27.2% of subjects experienced nausea or vomiting with semaglutide 0.5 and 1.0 mg, respectively, versus 6.0% to 14.1% with comparators. Only 0.07 to 0.5 kg of the treatment difference between semaglutide and comparators was mediated by nausea or vomiting (indirect effects). CONCLUSIONS: In SUSTAIN 1 to 5, semaglutide-induced weight loss was consistently greater versus comparators, regardless of baseline BMI. The contribution of nausea or vomiting to this weight loss was minor.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".