Cardiovascular Events Associated With SGLT-2 Inhibitors Versus Other Glucose-Lowering Drugs
Bibliographic record
Abstract
BACKGROUND: Randomized trials demonstrated a lower risk of cardiovascular (CV) events with sodium-glucose cotransporter-2 inhibitors (SGLT-2i) in patients with type 2 diabetes (T2D) at high CV risk. Prior real-world data suggested similar SGLT-2i effects in T2D patients with a broader risk profile, but these studies focused on heart failure and death and were limited to the United States and Europe. OBJECTIVES: The purpose of this study was to examine a broad range of CV outcomes in patients initiated on SGLT-2i versus other glucose-lowering drugs (oGLDs) across 6 countries in the Asia Pacific, the Middle East, and North American regions. METHODS: New users of SGLT-2i and oGLDs were identified via claims, medical records, and national registries in South Korea, Japan, Singapore, Israel, Australia, and Canada. Propensity scores for SGLT-2i initiation were developed in each country, with 1:1 matching. Hazard ratios (HRs) for death, hospitalization for heart failure (HHF), death or HHF, MI, and stroke were assessed by country and pooled using weighted meta-analysis. RESULTS: After propensity-matching, there were 235,064 episodes of treatment initiation in each group; ∼27% had established CV disease. Patient characteristics were well-balanced between groups. Dapagliflozin, empagliflozin, ipragliflozin, canagliflozin, tofogliflozin, and luseogliflozin accounted for 75%, 9%, 8%, 4%, 3%, and 1% of exposure time in the SGLT-2i group, respectively. Use of SGLT-2i versus oGLDs was associated with a lower risk of death (HR: 0.51; 95% confidence interval [CI]: 0.37 to 0.70; p < 0.001), HHF (HR: 0.64; 95% CI: 0.50 to 0.82; p = 0.001), death or HHF (HR: 0.60; 95% CI: 0.47 to 0.76; p < 0.001), MI (HR: 0.81; 95% CI: 0.74 to 0.88; p < 0.001), and stroke (HR: 0.68; 95% CI: 0.55 to 0.84; p < 0.001). Results were directionally consistent across both countries and patient subgroups, including those with and without CV disease. CONCLUSIONS: In this large, international study of patients with T2D from the Asia Pacific, the Middle East, and North America, initiation of SGLT-2i was associated with a lower risk of CV events across a broad range of outcomes and patient characteristics. (Comparative Effectiveness of Cardiovascular Outcomes in New Users of SGLT-2 Inhibitors [CVD-REAL]; NCT02993614).
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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 | 0.007 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.008 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".