Survodutide for treatment of obesity: Baseline characteristics of participants in a randomized, double‐blind, placebo‐controlled, phase 3 trial ( <scp>SYNCHRONIZE</scp> ™‐1)
Bibliographic record
Abstract
Abstract Aims Survodutide, a novel glucagon receptor and glucagon‐like peptide‐1 (GLP‐1) receptor dual agonist, elicited significant weight loss in a phase 2 trial in individuals with obesity without type 2 diabetes (T2D). Two multinational phase 3 trials are investigating survodutide for obesity management in individuals with or without T2D. We report the baseline characteristics of participants in the SYNCHRONIZE‐1 trial in adults with obesity without T2D ( ClinicalTrials.gov : NCT06066515). Materials and methods Participants aged ≥18 years with BMI ≥30 or ≥27 kg/m 2 with ≥1 obesity complication without T2D were randomized 1:1:1 to double‐blind, once‐weekly, subcutaneous injections of survodutide (up‐titrated to 3.6 or 6.0 mg) or placebo for 76 weeks. The primary endpoints are percent body weight change and achievement of body weight reduction ≥5% from baseline to Week 76. Efficacy and safety analyses will include all randomized and treated participants. Results At baseline, participants ( n = 725 from 14 countries) had a mean age of 47.1 years, BMI 37.9 kg/m 2 , and waist circumference 115.2 cm. Most participants (59.4%) were female; 47.3% were from North America, 21.0% from Europe, and 20.0% from East Asia. Obesity complications included hypertension (40.0%), dyslipidaemia (33.7%), and prediabetes (30.2%). Mean haemoglobin A1c was 5.5%, estimated glomerular filtration rate 93.0 mL/min/1.73 m 2 , systolic/diastolic blood pressure 127.0/82.7 mmHg, and low‐density lipoprotein cholesterol 116.4 mg/dL; 21.8% were taking lipid‐lowering drugs. Conclusions SYNCHRONIZE‐1 will determine the efficacy, safety, and tolerability of survodutide, a glucagon receptor/GLP‐1 receptor dual agonist, for weight loss in a representative cohort of people with obesity without T2D.
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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 | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".