P6270Empagliflozin reduces the total burden of first and recurrent hospitalisations in patients with type 2 diabetes and established cardiovascular disease
Bibliographic record
Abstract
Abstract Background and aims The EMPA-REG OUTCOME trial included patients with type 2 diabetes (T2D) and established atherosclerotic cardiovascular (CV) disease. Empagliflozin reduced the risk of 3-point major adverse CV events (MACE; composite of CV death, myocardial infarction [MI], or stroke) by 14%, CV death by 38% and hospitalisation for heart failure (HF) by 35% vs placebo in analyses of time to first event. We assessed the effect of empagliflozin on all-cause hospitalisation in post-hoc analyses of all (first and recurrent) events. Materials and methods Patients were randomised to receive empagliflozin 10 mg, empagliflozin 25 mg, or placebo in addition to standard of care. We assessed the effects of empagliflozin pooled vs placebo on first event of all-cause hospitalisation using Cox regression and all (first and recurrent) events of all-cause hospitalisation using a negative binomial model. Results A total of 7020 patients were treated (4687 empagliflozin; 2333 placebo, mean [SD] age 63 [9] years, 71% male, 47% with history of MI, 23% with history of stroke, 10% with HF). In this analysis, 1725/4687 (36.8%) empagliflozin patients and 925/2333 (39.6%) placebo patients experienced an event leading to hospitalisation. The adjusted hazard ratio (HR; 95% CI) vs placebo for first all-cause hospitalisation using the Cox regression model was 0.89 (0.82, 0.96; p=0.0033; Figure); In analyses of all (first and recurrent) hospitalisation events, there were 3168 events in the empagliflozin group and 1863 in the placebo group. The adjusted event rate ratio (95% CI) vs placebo was 0.83 (0.76, 0.91; p<0.0001; Figure). Conclusion In the EMPA-REG OUTCOME trial, risk reductions with empagliflozin were seen in both first and all hospitalisation events and were numerically more favourable in analyses of all events vs analyses of first events. These analyses expand on the favourable CV effects of empagliflozin by also showing a reduction in the total burden of hospitalisation events in patients with T2D and established CV disease. Acknowledgement/Funding Boehringer Ingelheim & Eli Lilly and Company Diabetes Alliance
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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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".