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Record W4414663736 · doi:10.1186/s12933-025-02900-8

Cardiovascular and renal outcomes of dual combination therapies with glucagon-like peptide-1 receptor agonists and sodium-glucose transport protein 2 inhibitors: a systematic review and meta-analysis

2025· review· en· W4414663736 on OpenAlexaff
Arveen Shokravi, Jayant Seth, G.B.John Mancini

Bibliographic record

VenueCardiovascular Diabetology · 2025
Typereview
Languageen
FieldMedicine
TopicDiabetes Treatment and Management
Canadian institutionsUniversity of British ColumbiaUniversity of British Columbia Hospital
Fundersnot available
KeywordsClinical trialAngiologyMEDLINEDual (grammatical number)Type 2 diabetesDiabetes mellitusRandomized controlled trialProspective cohort study

Abstract

fetched live from OpenAlex

BACKGROUND: Combination therapy with glucagon-like peptide-1 receptor agonists (GLP-1RA), sodium-glucose co-transporter 2 inhibitors (SGLT2i), and/or finerenone offers a strategy to reduce the risk of adverse cardiovascular and renal outcomes. This study aimed to quantify the cardiorenal benefits of combination regimens with GLP-1RA, SGLT2i, and/or finerenone versus corresponding monotherapies. METHODS: MEDLINE and Embase were systematically searched, yielding four post hoc analyses of randomized controlled trials (RCTs) and ten observational studies that met prespecified inclusion criteria. Among RCTs, a random-effects meta-regression was performed to assess whether the effect of GLP-1RAs on cardiorenal outcomes differed based on baseline SGLT2i use. Additionally, for observational studies, random-effects meta-analyses were performed to estimate the effect of combination therapy versus monotherapy on the risk of cardiorenal outcomes. RESULTS: Across RCTs, p for interaction was > 0.05 for major adverse cardiac events (MACE) (p = 0.730), cardiovascular (CV) mortality (p = 0.889), non-fatal myocardial infarction (MI) (p = 0.237), non-fatal stroke (p = 0.696), all-cause mortality (p = 0.682), heart failure (HF) hospitalization (p = 0.257), and renal composite outcome (p = 0.890), supporting that GLP-1RAs result in a consistent reduction in outcomes irrespective of baseline SGLT2i use. In observational trials, compared to SGLT2i monotherapy, GLP-1RA and SGLT2i combination therapy significantly reduced MACE (HR 0.59, 95% CI 0.47-0.75), MI (HR 0.73, 95% CI 0.61-0.88), stroke (HR 0.72, 95% CI 0.53-0.97), all-cause mortality (HR 0.57, 95% CI 0.48-0.67), and HF hospitalization/events (HR 0.71, 95% CI 0.59-0.86). Compared to GLP-1RA monotherapy, SGLT2i and GLP-1RA combination therapy significantly reduced CV mortality (HR 0.35, 95% CI 0.15-0.81), MI (HR 0.93, 95% CI 0.88-0.97), stroke (HR 0.92, 95% CI 0.88-0.96), all-cause mortality (HR 0.59, 95% 0.49-0.70), HF hospitalization/events (HR 0.84, 95% CI 0.81-0.88), and serious renal events (HR 0.43, 95% CI 0.23-0.80). Compared to either SGLT2i or finerenone monotherapy, SGLT2i and finerenone combination therapy significantly reduced all-cause mortality and major adverse kidney events. CONCLUSION: Combination therapy with GLP-1RA, SGLT2i, or finerenone confers cardiorenal protection beyond monotherapy in T2D, as supported by concordant evidence from RCTs and large real-world cohorts. These findings support broader clinical adoption of dual-agent strategies but also underscore the need for dedicated prospective trials powered to assess hard clinical outcomes with dual-agent strategies.

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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Meta-epidemiology (broad)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Meta-analysis · Consensus signal: Meta-analysis
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.423
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0230.009
Bibliometrics0.0010.001
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 head0.021
GPT teacher head0.262
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 teacher head, not a consensus.

Study designMeta-analysis
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

Citations10
Published2025
Admission routes1
Has abstractyes

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