Baseline characteristics in the <scp>SYNCHRONIZE</scp> ™‐2 randomized phase 3 trial of survodutide, a glucagon receptor/ <scp>GLP</scp> ‐1 receptor dual agonist, for obesity in people with type 2 diabetes
Bibliographic record
Abstract
AIMS: Survodutide is an investigational glucagon receptor/glucagon-like peptide-1 receptor dual agonist that has shown promise for treating obesity and its complications in Phase 2 trials. Two double-blind, randomized, global Phase 3 trials are designed to assess the efficacy and safety of survodutide for treatment of obesity-SYNCHRONIZE™-1 in people with obesity without type 2 diabetes (T2D) and SYNCHRONIZE™-2 in people with obesity and T2D. This paper describes the baseline characteristics of participants in SYNCHRONIZE-2 (ClinicalTrials.gov identifier NCT06066528). MATERIALS AND METHODS: and T2D were randomized 1:1:1 to weekly subcutaneous survodutide (up-titrated to 3.6 or 6.0 mg) or placebo with recommendations for modified diet and physical activity. The primary endpoints are the percentage change in body weight (BW) and achievement of BW reduction of ≥5% from baseline to Week 76. RESULTS: , BW 104.1 kg, waist circumference 115.5 cm and haemoglobin A1c 7.4%; 50.7% were female. Overall, 36.2% are from Europe, 32.8% from North America and 22.3% from East Asia. The most common obesity complications included hypertension (69.0%), dyslipidaemia (67.6%), obstructive sleep apnoea (17.3%) and arteriosclerotic cardiovascular disease (10.9%); 78.7% were treated with metformin, 34.2% with sodium-glucose co-transporter-2 inhibitors and 58.6% with lipid-lowering medications. CONCLUSIONS: SYNCHRONIZE-2 will determine the efficacy, safety and tolerability of survodutide for BW reduction in people with obesity and T2D, whose baseline characteristics suggest a representative, diverse cohort.
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.011 | 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".