Effect of empagliflozin on total myocardial infarction events by type and additional coronary outcomes: insights from the randomized EMPA-REG OUTCOME trial
Bibliographic record
Abstract
BACKGROUND: The effect of empagliflozin, a sodium-glucose-co-transporter-2 inhibitor, on risk for myocardial infarction has not been fully characterized. METHODS: This study comprised prespecified and post-hoc analyses of the EMPA-REG OUTCOME trial in which 7020 people with type 2 diabetes (T2D) and cardiovascular disease [mostly atherosclerotic (ASCVD)] were randomized to empagliflozin or placebo and followed for a median 3.1 years. We assessed the effect of empagliflozin on total (first plus recurrent) events of centrally adjudicated fatal and non-fatal myocardial infarction (MI) using a negative binomial model with robust confidence intervals (CI) that preserves randomization and accounts for the within-patient correlation of multiple events. Post hoc, we analyzed types of MI: type 1 (related to plaque-rupture/thrombus), type 2 (myocardial supply-demand imbalance), type 3 (sudden-death related, i.e. fatal MI), type 4 (percutaneous coronary intervention-related), and type 5 (coronary artery bypass graft-related). MIs could be assigned to > 1 type. RESULTS: There were 421 total MIs (including recurrent); 299, 86, 26, 19, and 1 were classified as type 1, 2, 3, 4, and 5 events, respectively. Overall, empagliflozin reduced the risk of total MI events by 21% [rate ratio for empagliflozin vs. placebo, 0.79 (95% CI, 0.620-0.998), P = 0.0486], largely driven by its effect on type 1 [rate ratio, 0.79 (95% CI, 0.61-1.04)] and type 2 MIs [rate ratio, 0.67 (95% CI, 0.41-1.10)]. CONCLUSIONS: In T2D patients with ASCVD, empagliflozin reduced the risk of MIs, with consistent effects across the two most common etiologies, i.e. type 1 and 2. TRAIL REGISTRATION: URL: https://www. CLINICALTRIALS: gov ; Unique identifier: NCT01131676.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".