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Record W4407162002 · doi:10.7759/cureus.78570

Comparing Glucagon-Like Peptide-1 Receptor Agonists to Sodium-Glucose Cotransporter-2 Inhibitors in Heart Failure With Preserved Ejection Fraction: A Systematic Review

2025· review· en· W4407162002 on OpenAlexaboutno aff
Moath Al-Shudifat, Bushra Sumra, Cyril Kocherry, Hina Shamim, Kiran Jhakri, Safeera Khan

Bibliographic record

VenueCureus · 2025
Typereview
Languageen
FieldMedicine
TopicDiabetes Treatment and Management
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineHeart failureEjection fractionGlucagon-like peptide-1Internal medicineEndocrinologyGlucagonReceptorPharmacologyCardiologyDiabetes mellitusType 2 diabetesInsulin

Abstract

fetched live from OpenAlex

Heart failure with preserved ejection fraction (HFpEF) is a subtype of congestive heart failure distinguished by a normal ejection fraction. Comorbidities associated with its development typically include chronic conditions such as diabetes, hypertension and obesity that restrict the heart's filling pressure. Since heart failure with reduced ejection fraction (HFrEF) has been the subject of much research, physicians have always been faced with the problem of a lack of effective therapeutic interventions when treating patients with HFpEF. In recent years, there has been an increase in the number of research studies to identify effective therapeutic medication for HFpEF. Sodium-glucose cotransporter-2 (SGLT-2) inhibitors and glucagon-like peptide-1 (GLP-1) receptor agonists, which were initially developed to manage diabetes, have shown improvement in clinical outcomes in HFpEF even in the absence of diabetes. This systematic review aimed to gather and analyze evidence from randomized controlled trials and observational studies on the two drug classes. The Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) 2020 guidelines were followed in the conduct of this comprehensive systematic review. To find all relevant studies, we searched three major medical databases, including Web of Science, Cochrane Central Register of Controlled Trials (CENTRAL), and PubMed (NCBI). We have identified 13 studies on both classes of drugs, some of which have contributed to formulating current guidelines for managing HFpEF. The quality of included studies has been scrutinized using quality assessment tools, including the Cochrane Risk of Bias 2 tool and the Newcastle-Ottawa Scale tool, to ensure transparency and limit bias to lead to more reliable findings. Most studies on SGLT-2 inhibitors demonstrated a significant reduction in hospitalization rates and symptom burden, as measured by Kansas City Cardiomyopathy Questionnaire (KCCQ) scores and functional capacity, as measured by a 6-minute walk test distance. GLP-1 receptor agonists have also improved symptom scores and functional capacity, specifically in obese patients, although reductions in hospitalization rates remain unclear. Improvements in functional capacity and symptom scores were observed for both drug classes, though some metrics were not consistently statistically significant across studies. The superiority of one medication over another remains inconclusive due to a lack of trials comparing both drugs. In addition, GLP-1 receptor agonists have been more recently studied, necessitating further research on this drug class to assess long-term outcomes, efficacy in non-obese patients, and combination with SGLT-2 inhibitors.

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)0.007
metaresearch head score (Gemma)0.026
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.016
Threshold uncertainty score0.036

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0070.026
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0160.015
Bibliometrics0.0070.007
Science and technology studies0.0010.001
Scholarly communication0.0030.002
Open science0.0020.001
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0060.000

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 head0.029
GPT teacher head0.302
Teacher spread0.272 · 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 designSystematic review
Domainnot available
GenreReview

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

Citations0
Published2025
Admission routes1
Has abstractyes

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