Real-world effectiveness of adding newer generation GLP-1RA to SGLT2i in type 2 diabetes
Bibliographic record
Abstract
Abstract Background Guidelines recommend combination therapy with glucagonlike peptide-1 receptor agonists (GLP-1RAs) and sodium-glucose cotransporter 2 inhibitors (SGLT2is) for cardiorenal risk reduction in people with type 2 diabetes (T2D); however, there is limited real-world evidence on the long-term effects of combination therapy on cardiometabolic and renal outcomes. The objective of this study was to assess cardiovascular (CV), metabolic, and renal effects of combination therapy with newer generation GLP-1RA (including once-weekly GLP-1RAs, once-daily oral semaglutide, and dual GLP-1/glucose-dependent insulinotropic polypeptide [GIP] agonists) and SGLT2i compared with SGLT2i alone. Methods This retrospective cohort study included data on US adults with T2D receiving SGLT2i from Komodo’s Healthcare Map from January 1, 2017, to June 30, 2023. The study included 100,455 people in the combination GLP-1RA and SGLT2i group and 339,540 people in the comparison SGLT2i group across 3 cohorts: T2D with atherosclerotic cardiovascular disease (ASCVD), T2D, and T2D with chronic kidney disease (CKD). Entropy balancing was used to balance patient characteristics. Time to first event of ischemic stroke, myocardial infarction (MI), 3-point major adverse cardiovascular event (MACE), and 5-point MACE in T2D with ASCVD cohort were measured. In the T2D cohort, follow-up and change in glycated hemoglobin (HbA 1c ) and weight, odds of achieving HbA 1c < 7% and HbA 1c < 8%, and odds of achieving 5%, 10%, and 15% decrease in weight were also measured. Results The combination and comparison groups included 34,690 and 130,220 people, respectively, in the T2D with ASCVD cohort; 8,220 and 22,891 people, respectively, in the T2D cohort; and 8,783 and 35,532 people, respectively, in the T2D with CKD cohort. Compared with SGLT2i alone, combination therapy was significantly associated with 42% lower risk of ischemic stroke, 37% lower risk of MI, 46% lower risk of 3-point MACE, and 45% lower risk of 5-point MACE among people with T2D and ASCVD. Among the individual GLP-1RAs assessed, the largest reductions in CV risk, HbA 1c , and weight outcomes were observed with combination therapy with SGLT2i and once weekly semaglutide for T2D. Conclusions Combination of SGLT2i and GLP-1RA achieved significantly better cardiometabolic outcomes compared with SGLT2i alone; this supports the hypothesis that the cardioprotective benefits of GLP-1RA and SGLT2i may be additive. Graphical abstract
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".