Empagliflozin in patients with type 2 diabetes mellitus and chronic obstructive pulmonary disease
Bibliographic record
Abstract
AIMS: Type 2 diabetes mellitus (T2DM) and chronic obstructive pulmonary disease (COPD) often co-exist, yielding increased risk of cardiovascular (CV) complications including heart failure (HF). We assessed risk of cardiorenal outcomes, mortality and safety in patients with versus without COPD in the EMPA-REG OUTCOME trial. METHODS: Patients (n = 7,020) with T2DM and CV disease (CVD) were treated with empagliflozin (10 mg or 25 mg) or placebo. Cox regression was used to assess COPD subgroup (placebo only) associations with, and treatment effects of empagliflozin versus placebo on first hospitalization for HF (HHF), CV death, all-cause mortality, incident/worsening nephropathy, and all-cause hospitalization. RESULTS: At baseline, patients with COPD (n = 707) had more HF and used insulin more frequently than those without COPD. During follow-up in the placebo group, those with baseline COPD had increased risk of HHF (HR 2.15 [95% CI 1.32, 3.49]), HHF/CV death (1.60 [1.10, 2.33]), incident/worsening nephropathy (1.68 [1.26, 2.24]), all-cause hospitalization (1.44 [1.19, 1.74]) and all-cause death (1.60 [1.09, 2.35]) compared to those without COPD. Empagliflozin consistently reduced all clinical outcomes, irrespective of COPD status (interaction p-values 0.14 to 0.96), with a confirmed safety profile. CONCLUSIONS: In patients with T2DM and CVD, COPD increased the risk of mortality and cardiorenal outcomes, including HF. Empagliflozin consistently reduced these outcomes versus placebo regardless of COPD, suggesting that empagliflozin's benefits in patients with T2DM and CVD are not mitigated by the presence of COPD.
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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 | 0.002 |
| 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) | 0.001 | 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".