Mediators of the Improvement in Heart Failure Outcomes with Empagliflozin in the EMPA-REG OUTCOME Trial
Bibliographic record
Abstract
AIMS: In the EMPA-REG OUTCOME trial, empagliflozin reduced risk of death from heart failure (HF) or hospitalization for heart failure (HHF) versus placebo in patients with type 2 diabetes mellitus (T2DM) and established cardiovascular (CV) disease. We evaluated post hoc the degree to which covariates mediated the effects of empagliflozin on HHF or HF death. METHODS AND RESULTS: A mediator had to fulfil the following criteria: (i) affected by active treatment, (ii) associated with the outcome, and finally (iii) adjustment for it results in a reduced treatment effect compared with unadjusted analysis. Potential mediators were calculated as change from baseline or updated mean and evaluated in univariable analyses as time-dependent covariates in Cox regression of time to HHF or HF death; those with the largest mediating effects were then included in a multivariable analysis. Increases in heart rate, log urine albumin-to-creatinine ratio (UACR), waist circumference, and uric acid were associated with increased risk of HHF or HF death; increases in high-density lipoprotein cholesterol, estimated glomerular filtration rate, haematocrit, haemoglobin, and albumin were associated with reduced risk of HHF or HF death. In univariable analyses, change from baseline in haematocrit, haemoglobin, albumin, uric acid, and logUACR mediated 51%, 54%, 23%, 24%, and 27% of the risk reduction with empagliflozin versus placebo, respectively. Multivariable analysis including haemoglobin, logUACR, and uric acid mediated 85% of risk reduction with similar results when updated means were evaluated. CONCLUSIONS: Changes in haematocrit and haemoglobin were the most important mediators of the reduction in HHF and death from HF in patients with T2DM and established CV disease treated with empagliflozin. Albumin, uric acid, and logUACR had smaller mediating effects in this population.
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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 | 0.003 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| 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 | 0.002 |
| 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".