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Record W4403673786 · doi:10.1016/j.jchf.2024.09.004

Survodutide for the Treatment of Obesity

2024· article· en· W4403673786 on OpenAlexaff
Mikhail Kosiborod, Elke Platz, Sean Wharton, Carel W. le Roux, Martina Brueckmann, Samina Ajaz Hussain, Anna Unseld, Elena Startseva, Lee M. Kaplan

Bibliographic record

VenueJACC Heart Failure · 2024
Typearticle
Languageen
FieldMedicine
TopicPharmacology and Obesity Treatment
Canadian institutionsUniversity of Toronto
FundersBoehringer Ingelheim
KeywordsMedicineHeart failureObesityIntensive care medicineInternal medicine

Abstract

fetched live from OpenAlex

Dual agonism of glucagon and glucagon-like peptide-1 (GLP-1) receptors may be more effective than GLP-1 receptor agonism alone in reducing body weight, but the cardiovascular (CV) effects are unknown. The authors describe the rationale and design of SYNCHRONIZE-CVOT, a phase 3, randomized, double-blind, parallel-group, event-driven, CV safety study of survodutide, a dual glucagon and GLP-1 receptor agonist, administered subcutaneously once weekly compared with placebo in adults with a body mass index ≥27 kg/m2 and established CV disease or chronic kidney disease, and/or at least 2 weight-related complications or risk factors for CV disease. The primary endpoint of SYNCHRONIZE-CVOT is time to first occurrence of the composite adjudicated endpoint of 5-point major adverse CV events. This global CV outcomes trial is currently enrolling, with a target recruitment of 4,935 participants. SYNCHRONIZE-CVOT is the first trial that will determine the CV safety and efficacy of survodutide in people with obesity and increased CV risk. (A Study to Test the Effect of Survodutide [BI 456906] on Cardiovascular Safety in People With Overweight or Obesity [SYNCHRONIZE–CVOT]; NCT06077864)

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.226
Threshold uncertainty score0.244

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.027
GPT teacher head0.339
Teacher spread0.313 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreEmpirical

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".

Quick stats

Citations30
Published2024
Admission routes1
Has abstractyes

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