Empagliflozin and Kidney Function Decline in Patients with Type 2 Diabetes: A Slope Analysis from the EMPA-REG OUTCOME Trial
Bibliographic record
Abstract
Background Empagliflozin slowed the progression of CKD in patients with type 2 diabetes and cardiovascular disease in the EMPA-REG OUTCOME Trial. In a prespecified statistical approach, we assessed treatment differences in kidney function by analyzing slopes of eGFR changes. Methods Participants ( n =7020) were randomized (1:1:1) to empagliflozin 10 mg/d, empagliflozin 25 mg/d, or placebo added to standard of care. We calculated eGFR slopes using random-intercept/random-coefficient models for prespecified study periods: treatment initiation (baseline to week 4), chronic maintenance treatment (week 4 to last value on treatment), and post-treatment (last value on treatment to follow-up). Results Compared with placebo, empagliflozin was associated with uniform shifts in individual eGFR slopes across all periods. On treatment initiation, adjusted mean slope (eGFR change per week, ml/min per 1.73 m 2 ) decreased with empagliflozin (−0.77; 95% confidence interval, −0.83 to −0.71; placebo: 0.01; 95% confidence interval, −0.08 to 0.10; P <0.001). However, annual mean slope (ml/min per 1.73 m 2 per year) did not decline with empagliflozin during chronic treatment (empagliflozin: 0.23; 95% confidence interval, 0.05 to 0.40; placebo: −1.46; 95% confidence interval, −1.74 to −1.17; P <0.001). After drug cessation, the adjusted mean eGFR slope (ml/min per 1.73 m 2 per week) increased and mean eGFR returned toward baseline level only in the empagliflozin group (0.56; 95% confidence interval, 0.49 to 0.62; placebo −0.02; 95% confidence interval, −0.12 to 0.08; P <0.001). Results were consistent across patient subgroups at higher CKD risk. Conclusions The hemodynamic effects of empagliflozin, associated with reduction in intraglomerular pressure, may contribute to long-term preservation of kidney function.
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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 | 0.010 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.005 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".