Cardiovascular outcomes with sodium–glucose cotransporter-2 inhibitors vs other glucose-lowering drugs in 13 countries across three continents: analysis of CVD-REAL data
Bibliographic record
Abstract
Abstract Background Randomized, controlled cardiovascular outcome trials may not be fully representative of the management of patients with type 2 diabetes across different geographic regions. We conducted analyses of data from the multinational CVD-REAL consortium to determine the association between initiation of sodium–glucose cotransporter-2 inhibitors (SGLT-2i) and cardiovascular outcomes, including subgroup analyses based on patient characteristics. Methods De-identified health records from 13 countries across three continents were used to identify patients newly-initiated on SGLT-2i or other glucose-lowering drugs (oGLDs). Propensity scores for SGLT-2i initiation were developed in each country, with 1:1 matching for oGLD initiation. In the matched groups hazard ratios (HRs) for hospitalization for heart failure (HHF), all-cause death (ACD), the composite of HHF or ACD, myocardial infarction (MI) and stroke were estimated by country, and pooled using a weighted meta-analysis. Multiple subgroup analyses were conducted across patient demographic and clinical characteristics to examine any heterogeneity in treatment effects. Results Following matching, 440,599 new users of SGLT-2i and oGLDs were included in each group. Mean follow-up time was 396 days for SGLT-2i initiation and 406 days for oGLDs initiation. SGLT-2i initiation was associated with a lower risk of HHF (HR: 0.66, 95%CI 0.58–0.75; p < 0.001), ACD (HR: 0.52, 95%CI 0.45–0.60; p < 0.001), the composite of HHF or ACD (HR: 0.60, 95%CI 0.53–0.68; p < 0.001), MI (HR: 0.85, 95%CI 0.78–0.92; p < 0.001), and stroke (HR: 0.78, 95%CI 0.72–0.85; p < 0.001); regardless of patient characteristics, including established cardiovascular disease, or geographic region. Conclusions This CVD-REAL study extends the findings from the SGLT-2i clinical trials to the broader setting of an ethnically and geographically diverse population, and across multiple subgroups. Trial registration NCT02993614
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 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 | 0.018 | 0.018 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.011 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".