Effect of empagliflozin on cardiac remodelling in South Asian and non-South Asian individuals: insights from the EMPA-HEART CardioLink-6 randomised clinical trial
Bibliographic record
Abstract
Abstract Background This exploratory sub-analysis of the EMPA-HEART CardioLink-6 trial examined whether the previously reported benefit of the sodium-glucose cotransporter 2 (SGLT2) inhibitor empagliflozin on left ventricular (LV) mass (LVM) regression differs between individuals of South Asian and non-South Asian ethnicity. Methods EMPA-HEART CardioLink-6 was a double-blind, placebo-controlled clinical trial that randomised 97 individuals with type 2 diabetes mellitus (T2DM) and coronary artery disease (CAD) to either empagliflozin 10 mg daily or placebo for 6 months. LV parameters and function were assessed using cardiac magnetic resonance imaging. The 6-month changes in LVM and LV volumes, all indexed to baseline body surface area, for South Asian participants were compared to those for non-South Asian individuals. Results Compared to the non-South Asian group, the South Asian sub-cohort comprised more males, was younger and had a lower median body mass index. The adjusted difference for LVMi change over 6 months was -4.3 g/m2 (95% confidence interval [CI], -7.5, -1.0; P = 0.042) for the South Asian group and -2.3 g/m2 (95% CI, -6.4, 1.9; P = 0.28) for the non-South Asian group (Pinteraction = 0.45). There was no between-group difference for the adjusted differences in baseline body surface area-indexed LV volumes and LV ejection fraction. Conclusions There was no meaningful difference in empagliflozin-associated LVM regression between South Asian and non-South Asian individuals living with T2DM and CAD in the EMPA-HEART CardioLink-6 trial. Trial registration ClinicalTrials.gov Identifier: NCT02998970 (First posted on 21/12/ 2016).
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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 | 0.005 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.004 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".