Achieving glycaemic control without weight gain, hypoglycaemia, or gastrointestinal adverse events in type 2 diabetes in the SUSTAIN clinical trial programme
Bibliographic record
Abstract
AIM: To evaluate the potential for semaglutide to help people with type 2 diabetes (T2D) achieve glycated haemoglobin (HbA1c) targets while avoiding unwanted outcomes, such as weight gain, hypoglycaemia and gastrointestinal (GI) side effects. MATERIALS AND METHODS: Data from the phase IIIa SUSTAIN 1 to 5 clinical trials were analysed. Participants had inadequately controlled T2D and were drug-naïve (SUSTAIN 1) or on a range of background treatments (SUSTAIN 2 to 5). The main protocol-specified composite endpoint was the proportion of participants achieving HbA1c <53 mmol/mol (7.0%) at end of treatment (30 or 56 weeks) without weight gain and with no severe or blood glucose (BG)-confirmed symptomatic hypoglycaemia. A post hoc composite endpoint was the proportion of participants achieving the primary composite endpoint without moderate or severe GI adverse events (AEs). RESULTS: Across the SUSTAIN trials 1 to 5, 3918 participants with T2D were randomized to once-weekly subcutaneous semaglutide 0.5 mg, 1.0 mg, or comparators (placebo, sitagliptin 100 mg, exenatide extended release 2.0 mg or insulin glargine). The proportion of participants achieving HbA1c <53 mmol/mol (7.0%) with no weight gain and no severe/BG-confirmed symptomatic hypoglycaemia was 47% to 66% (semaglutide 0.5 mg) and 57% to 74% (semaglutide 1.0 mg) vs 7% to 19% (placebo) and 16% to 29% (active comparators; all P < .0001). More participants achieved the primary composite endpoint with no moderate or severe GI AEs with semaglutide vs comparators (all P < .0001). CONCLUSION: Semaglutide helped more people with T2D achieve HbA1c targets than did comparators in the SUSTAIN 1 to 5 trials, while avoiding unwanted outcomes such as weight gain, hypoglycaemia and GI side effects.
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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 | 0.005 | 0.004 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.008 | 0.001 |
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".