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
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.010 | 0.019 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.020 | 0.039 |
| Bibliometrics | 0.007 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".