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Record W4414394366 · doi:10.1002/ejhf.70048

Effect of Glucagon-Like Peptide-1 Receptor Agonists on Heart Failure Outcomes and Cardiovascular Death Across Varying Cardiovascular-Kidney-Metabolic Comorbidity

2025· article· en· W4414394366 on OpenAlexaff
Tariq Jamal Siddiqi, Muhammad Shahzeb Khan, Shoaib Waqas, Harriette G.C. Van Spall, Michael D. Shapiro, Gregg C. Fonarow, James L. Januzzi, Aasim Afzal, Ambarish Pandey, Javed Butler, Stephen J. Greene

Bibliographic record

VenueEuropean Journal of Heart Failure · 2025
Typearticle
Languageen
FieldMedicine
TopicDiabetes Treatment and Management
Canadian institutionsMcMaster University
Fundersnot available
KeywordsHeart failureComorbidityAgonistReceptorCause of deathClinical trial

Abstract

fetched live from OpenAlex

AIMS: Effects of glucagon-like peptide-1 receptor agonists (GLP-1RAs) on heart failure hospitalization (HFH) and cardiovascular (CV) death among patients with varying overlap of cardiovascular-kidney-metabolic (CKM) comorbidity are not well characterized. This study aimed to assess effects GLP-1RAs on HFH and CV death across populations with varying type and number of CKM comorbidity. METHODS AND RESULTS: Online databases were queried through November 2024 for primary and secondary analyses of clinical outcome trials of GLP-1RAs in patients with heart failure (HF), type 2 diabetes mellitus (T2DM), chronic kidney disease (CKD), obesity, and combinations of these diseases. Primary outcome was a composite HFH or CV death. Secondary outcomes were first HFH and CV death. Hazard ratios (HRs), risk ratios (RRs), and their 95% confidence intervals (CI) were derived using random-effects models. Fifteen trials (n = 87 549) were included. Compared with placebo, GLP-1RAs reduced the relative risk of composite HFH/CV death in HF (HR 0.81, 95% CI 0.69-0.96), T2DM (HR 0.85, 95% CI 0.78-0.93), and obesity (HR 0.70, 95% CI 0.58-0.86), with a non-significant risk reduction in CKD (HR 0.79, 95% CI 0.61-1.01). GLP-1RAs reduced the risk of HFH in T2DM (HR 0.89, 95% CI 0.80-0.99) and obesity (HR 0.63, 95% CI 0.45-0.87), with a non-significant risk reduction among patients with HF (HR 0.85, 95% CI 0.69-1.04) and CKD (HR 0.82, 95% CI 0.64-1.06). GLP-1RAs also significantly reduced CV death in HF (HR 0.88, 95% CI 0.77-0.99), T2DM (HR 0.85, 95% CI 0.78-0.93), and in obesity (HR 0.83, 95% CI 0.73-0.93), with a non-significant risk reduction in CKD (HR 0.80, 95% CI 0.60-1.08). Effects were consistent across subgroups, except for HF with reduced ejection fraction (HFrEF), where GLP-1RAs showed a non-significant risk increase in HFH (HR 1.17, 95% CI 0.93-1.47) but significantly reduced CV death (HR 0.67, 95% CI 0.50-0.90). GLP-1RAs were not associated with increased risk for serious adverse events (RR 0.94, 95% CI 0.89-1.00). CONCLUSIONS: Glucagon-like peptide-1 receptor agonists reduce HFH and CV death across CKM conditions, with generally consistent effects in varying combinations of these diseases. The potential exception is among patients with HFrEF, where a reduction in risk of CV death, but a numeric increase in HFH, was observed. Definitive CV outcome trials are needed to definitively determine effects of GLP-1RAs in patients with established HFrEF.

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)0.015
metaresearch head score (Gemma)0.015
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 score0.015
Threshold uncertainty score0.077

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0150.015
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0030.006
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.010
GPT teacher head0.264
Teacher spread0.253 · 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

Citations11
Published2025
Admission routes1
Has abstractyes

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