Cardio-Kidney Effects of Dapagliflozin in Patients at Elevated Cardiovascular Risk with or Without Type 2 Diabetes
Bibliographic record
Abstract
Background: We investigated the physiological effects of 12 weeks of sodium-glucose cotransporter 2 inhibition (dapagliflozin 10mg daily) on cardiac, vascular, kidney, & neurohormonal pathways in participants at elevated cardiovascular (CV) risk. Methods: This randomized double-blind, parallel-group, placebo-controlled study enrolled 51 participants & comprised three sequential physiologic assessments under clamped euglycemia (4 to 6 mmol/l): baseline, at 1 week & 12 weeks of treatment. The primary outcome measured vascular arterial stiffness, captured by pulse wave velocity & augmentation indices. Secondary outcomes included: blood pressure (BP), body fluid composition, non-invasive cardiac output monitoring, arterial vasodilatation tests, heart rate variability, echocardiography, iohexol-measured glomerular filtration rate (GFR) & natriuresis. Results: Dapagliflozin decreased vascular arterial stiffness, as measured by aortic augmentation index (–7.38±2.84%, p=0.01), after 12 weeks. Dapagliflozin acutely decreased supine measures of systolic BP (9.38±3.84 mmHg) & extracellular fluid (–0.84±0.27 L), with sustained reductions in thoracic fluid content at 12 weeks (–3.25±1.47 1/kΩ). There was evidence of tubuloglomerular feedback activation with reductions in measured GFR (–5.82±2.11 ml/min/1.73m2), acute increases in proximal sodium excretion (5.10±2.22%) & absolute fractional distal sodium reabsorption (4.41±2.05%), & increases in urine adenosine. Conclusion: Dapagliflozin induced multiple mechanisms associated with CV & kidney protection in patients at varying levels of CV risk in whom evidence of clinical protection is lacking. Funding: Commercial Support - AstraZeneca
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 | 0.001 | 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".