Abstract 13520: Empagliflozin Reduces Markers of Arterial Stiffness, Vascular Resistance and Cardiac Workload in EMPA-REG OUTCOME
Bibliographic record
Abstract
Introduction: In EMPA-REG OUTCOME ® , empagliflozin added to standard of care in patients with type 2 diabetes and established vascular disease, significantly reduced the primary composite outcome of CV death, non-fatal myocardial infarction or non-fatal stroke, a result driven mainly by a 38% reduction in CV death. We aimed to assess the vascular effects of empagliflozin in the trial, beyond its recognized effects in reducing systolic blood pressure (SBP) and diastolic BP (DBP). Hypothesis: We hypothesized that empagliflozin reduced 1) pulse pressure (PP), a vascular marker of arterial stiffness determined by the cardiac output, the stiffness of elastic central arteries and wave reflection (PP = SBP - DBP), 2) mean arterial pressure (MAP), a measure reflecting the cardiac cycle determined by the cardiac output, systemic vascular resistance, and central venous pressure (MAP = ([2 x diastolic BP]+ systolic BP)/3), and 3) the double product (DP), a marker of cardiac workload and an indirect measure of myocardial oxygen demand (DP = heart rate x SBP). Methods: Patients with type 2 diabetes and high CV risk were randomised to receive placebo, empagliflozin 10 mg, or empagliflozin 25 mg in addition to standard of care. We analysed changes from baseline to week 164 for SBP, DBP, HR, PP, MAP and DP, between treatment and placebo groups using a mixed model repeated measures analysis. Results: In total, 2333, 2345 and 2342 patients received placebo, empagliflozin 10 mg and empagliflozin 25 mg, respectively and followed for a median period of 3.1 years. There were nominal significantly greater reductions in PP, MAP and DP with empagliflozin treatment as compared with placebo (Table), without increases in mean HR (Table). Conclusions: Empagliflozin had favorable effects on BP, arterial stiffness, vascular resistance and on the indirect measure of cardiac workload. Further analyses are needed to determine the potential contribution of these changes to the reduction in CV mortality.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".