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 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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| 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".