Abstract 12880: Left Ventricular Mass Predicts Cardiac Reverse Remodeling in Patients With Type 2 Diabetes and Coronary Artery Disease Who Are Treated With Empagliflozin
Bibliographic record
Abstract
Introduction: Left ventricular (LV) hypertrophy is associated with an elevated risk for cardiovascular disease and all-cause mortality. The cardiovascular benefits of sodium-glucose cotransporter protein-2 (SGLT2) inhibitors have been attributed, in part, to cardiac reverse remodeling. The EMPA-HEART CardioLink-6 study previously reported that SGLT2 inhibition with empagliflozin for 6 months was associated with a significant reduction in LV mass indexed to body surface area (LVMi). We sought to determine in the same cohort if baseline LVMi influences empagliflozin-associated cardiac reverse remodelling. Methods: A total of 97 patients with type 2 diabetes and coronary artery disease was randomized to empagliflozin (10 mg/d) or matching placebo for 6 months in the EMPA-HEART CardioLink-6 study. This cohort was stratified into those with baseline LVMi <60 g/m 2 and those with LVMI ≥60 g/m 2 . Between-group comparisons were conducted using a linear regression model adjusted for baseline differences in LVMi (ANCOVA) that included an interaction term between baseline LVMi sub-group and treatment. Results: The effect empagliflozin had on the change in LVMi over 6 months was significantly different between patients with a baseline LVMi <60 g/m 2 and those whose LVMi was ≥60 g/m 2 . The adjusted difference between those randomized to empagliflozin and those assigned placebo after multivariable adjustment for baseline characteristics was 0.59 g/m 2 (95% CI: -3.01 g/m 2 , 4.19 g/m 2 , P=0.74) and -7.03 g/m 2 (95% CI: -11.06 g/m 2 , -2.99 g/m 2 , P=0.001) in the LVMi <60 g/m 2 and LVMi ≥60 g/m 2 subgroups, respectively (P interaction =0.0054). No significant association was found between baseline LVMi and 6-month change in LV end systolic volume-indexed (P interaction =0.086), LV end diastolic volume-indexed (P interaction =0.34), or LV ejection fraction (P interaction =0.15). Conclusions: In the EMPA-HEART CardioLink-6 cohort, greater cardiac reverse remodelling benefits were observed with empagliflozin in patients with higher baseline LVMi. Studies with larger cohorts and longer follow-ups are warranted to confirm the impact baseline LV mass has on SGLT2 inhibitor-associated remodelling.
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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 | 0.001 | 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".