Mechanistic evaluation of ertugliflozin in patients with type 2 diabetes and heart failure
Bibliographic record
Abstract
The effect of sodium-glucose cotransporter-2 (SGLT2) inhibitor ertugliflozin on fluid volume and kidney function was assessed in patients with type 2 diabetes and heart failure. Thirty-four participants were randomized in this double-blind, placebo-controlled, parallel-group, multicenter study. Physiologic measurements were obtained under clamped euglycemia at baseline, 1 week, and 12 weeks of treatment. The primary outcome was the proximal tubular natriuretic effect of ertugliflozin versus placebo, measured by fractional excretion of lithium (FELi). Ertugliflozin did not increase FELi or total FENa at 1 week or 12 weeks. Ertugliflozin increased both mean 24-h urinary sodium excretion (47.5 ± 22.1 mmol/day vs. placebo, p = 0.032) and urinary volume (p = 0.009) at 1 week, which was attenuated at Week 12. Reductions in extracellular fluid (-1.9 ± 0.8 L, p = 0.01), estimated plasma volume (-11.9 ± 13.9%, p = 0.02), and supine mean arterial pressure (-6.6 ± 2.7 mmHg, p = 0.02) were significant at Week 12. Compared to placebo, ertugliflozin acutely increased circulating angiotensinogen and angiotensin-converting enzyme (ACE) levels, as well as urine adenosine and ACE2 activity (p < 0.05). Changes in other neurohormones, sympathetic activity, kidney, and systemic hemodynamics did not differ compared to placebo. Our findings suggest that SGLT2 inhibition shifts systemic volume toward a state of euvolemia, potentially lowering the risk of worsening heart failure.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 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".