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Record W4396873474 · doi:10.1016/j.jacc.2024.04.022

Semaglutide and NT-proBNP in Obesity-Related HFpEF

2024· article· en· W4396873474 on OpenAlexaff
Mark C. Petrie, Barry A. Borlaug, Javed Butler, Melanie J. Davies, Dalane W. Kitzman, Sanjiv J. Shah, Subodh Verma, Thomas Jensen, Mette Nygaard Einfeldt, Karoline Liisberg, Eduardo Perna, Kavita Sharma, Justin A. Ezekowitz, Michael Fu, Vojtěch Melenovský, Hiroshi Ito, Małgorzata Lelonek, Mikhail Kosiborod

Bibliographic record

VenueJournal of the American College of Cardiology · 2024
Typearticle
Languageen
FieldMedicine
TopicDiabetes Treatment and Management
Canadian institutionsUniversity of TorontoUniversity of AlbertaSt. Michael's Hospital
FundersNovo Nordisk
KeywordsSemaglutideMedicineInternal medicineCardiologyPlaceboHeart failure with preserved ejection fractionHeart failureObesityWeight lossEjection fractionEndocrinologyType 2 diabetesDiabetes mellitusLiraglutide

Abstract

fetched live from OpenAlex

BACKGROUND: The glucagon-like peptide-1 receptor agonist, semaglutide, improved health status and reduced body weight in patients with obesity-related heart failure (HF) with preserved ejection fraction (HFpEF) in the STEP-HFpEF (Semaglutide Treatment Effect in People with Obesity and HFpEF) program. Whether benefits were due to mechanical unloading or effects on HF pathobiology is uncertain. OBJECTIVES: This study sought to determine if semaglutide 2.4 mg reduced N-terminal pro-B-type natriuretic peptide (NT-proBNP) in patients with obesity-related HFpEF and compare treatment responses by baseline NT-proBNP. METHODS: This was a prespecified secondary analysis of pooled data from 2 double-blind, placebo-controlled, randomized trials (STEP-HFpEF [Research Study to Investigate How Well Semaglutide Works in People Living With Heart Failure and Obesity] and STEP-HFpEF DM [Research Study to Look at How Well Semaglutide Works in People Living With Heart Failure, Obesity and Type 2 Diabetes]) testing effects of semaglutide in patients with obesity-related HFpEF. The main outcomes were change in NT-proBNP at 52 weeks and change in the dual primary endpoints of Kansas City Cardiomyopathy Questionnaire Clinical Summary Score and body weight by baseline NT-proBNP. RESULTS: In total, 1,145 patients were randomized. Semaglutide compared with placebo reduced NT-proBNP at 52 weeks (estimated treatment ratio: 0.82; 95% CI: 0.74-0.91; P = 0.0002). Improvements in health status were more pronounced in those with higher vs lower baseline NT-proBNP (estimated difference: tertile 1: 4.5 points, 95% CI: 0.8-8.2; tertile 2: 6.2 points, 95% CI: 2.4-10.0; tertile 3: 11.9 points, 95% CI: 8.1-15.7; P interaction = 0.02; baseline NT-proBNP as a continuous variable: P interaction = 0.004). Reductions in body weight were consistent across baseline NT-proBNP levels (P interaction = 0.21). CONCLUSIONS: In patients with obesity-related HFpEF, semaglutide reduced NT-proBNP. Participants with higher baseline NT-proBNP had a similar degree of weight loss but experienced larger reductions in HF-related symptoms and physical limitations with semaglutide than those with lower NT-proBNP.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.002
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.008
GPT teacher head0.249
Teacher spread0.241 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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

Citations82
Published2024
Admission routes1
Has abstractyes

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