Nephrotic-range proteinuria in type 2 diabetes: Effects of empagliflozin on kidney disease progression and clinical outcomes
Bibliographic record
Abstract
Background Diabetic kidney disease with nephrotic-range proteinuria (NRP) is commonly associated with rapid kidney function loss, increased cardiovascular risk, and premature mortality. We explored the effect of empagliflozin in patients with type 2 diabetes and cardiovascular disease, complicated by presence of this major risk factor for progressive kidney disease, in a post-hoc analysis of data from the EMPA-REG OUTCOME trial (NCT01131676). Methods Cox proportional hazards models were used to investigate the risk of cardiovascular and kidney outcomes in participants with and without NRP, defined by urine albumin-to-creatinine ratio (UACR) ≥2200 mg/g at baseline. Annual loss of eGFR during chronic treatment (eGFR slopes) and hypothetical time to projected end-stage kidney disease (ESKD), conditioning upon linearity of eGFR change over time if a patient did not decease before projected ESKD, were calculated using a random-intercept random-coefficient model. Safety was described based on investigator-reported adverse events. Findings 112 participants (pooled empagliflozin, n = 70; placebo, n = 42; median on-treatment follow-up of 1·9 years on placebo compared with 2·3 years on empagliflozin) presented with NRP at baseline; eGFR and UACR were balanced between treatments. Empagliflozin benefits on cardiovascular death, hospitalisation for heart failure, or kidney outcomes, were consistent in participants with and without NRP (p interaction >0·1). Treatment effects of empagliflozin on adjusted annual mean eGFR slope were more pronounced in participants with NRP versus those without (p interaction 0·005). Empagliflozin was estimated to double the median hypothetical time to projected ESKD in participants with NRP. The overall safety profile of empagliflozin was comparable between participants with and without NRP at baseline. Interpretation Our data suggests that empagliflozin might slow kidney function loss and delay the estimated onset of projected ESKD in patients with type 2 diabetes and cardiovascular disease complicated by NRP.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".