Effects of empagliflozin on insulin initiation or intensification in patients with type 2 diabetes and cardiovascular disease: Findings from the <scp>EMPA‐REG OUTCOME</scp> trial
Bibliographic record
Abstract
AIM: To evaluate the effects of empagliflozin versus placebo on subsequent insulin initiation or dosing changes in a large cardiovascular outcomes trial. MATERIALS AND METHODS: In EMPA-REG OUTCOME, 7020 patients with type 2 diabetes and cardiovascular disease received empagliflozin 10 mg, 25 mg, or placebo. Median follow-up was 3.1 years. After 12 weeks of treatment, changes in background antihyperglycaemic therapy were permitted. Among insulin-naïve patients, we assessed the effects of pooled empagliflozin arms versus placebo on time to initiation of insulin. Among insulin-treated patients, we assessed effects on time to an increase or decrease in insulin dose of more than 20%. RESULTS: In 3633 (52%) participants not treated with insulin at baseline, empagliflozin reduced new use of insulin versus placebo by 60% (7.1% vs. 16.4%; adjusted HR 0.40 [95% CI 0.32-0.49]; P < .0001). In 3387 (48%) patients using insulin at baseline, empagliflozin reduced the need for a greater than 20% insulin dose increase by 58% (14.4% vs. 29.3%; adjusted HR 0.42 [95% CI 0.36-0.49]; P < .0001) and increased the proportion achieving sustained greater than 20% insulin dose reductions without subsequent increases in HbA1c compared with placebo (9.2% vs. 4.9%; adjusted HR 1.87 [95% CI: 1.39-2.51]; P < .0001). Sensitivity analyses confirmed consistent findings when insulin dose changes of more than 10% or more than 30% were considered. CONCLUSIONS: In patients with type 2 diabetes and cardiovascular disease, empagliflozin markedly and durably delays insulin initiation and substantial increases in insulin dose, while facilitating sustained reductions in insulin requirements over time.
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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) | 0.002 | 0.004 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".