The Effect of Direct Renin Inhibition Alone and in Combination With ACE Inhibition on Endothelial Function, Arterial Stiffness, and Renal Function in Type 1 Diabetes
Bibliographic record
Abstract
OBJECTIVE: Diabetes is associated with renin-angiotensin system (RAS) activation, leading to renal and systemic vascular dysfunction that contribute to end-organ injury and significant morbidity. RAS blockade with ACE inhibitors reduces, but does not abolish, RAS effects. Accordingly, our aim was to determine if direct renin inhibition alone, and in combination with an ACE inhibitor, corrects early hemodynamic abnormalities associated with type 1 diabetes. RESEARCH DESIGN AND METHODS: Arterial stiffness (augmentation index), flow-mediated vasodilatation (FMD), and renal hemodynamic function (inulin and paraaminohippurate clearance) were measured at baseline under clamped euglycemic and hyperglycemic conditions (n = 21). Measures were repeated after 4 weeks of aliskiren therapy and again after aliskiren plus ramipril. RESULTS: Blood pressure-lowering effects of aliskiren were similar during clamped euglycemia and hyperglycemia. Combination therapy augmented this effect under both glycemic conditions (P = 0.0005). Aliskiren reduced arterial stiffness under clamped euglycemic and hyperglycemic conditions, and the effects were augmented by dual RAS blockade (-3.4 ± 11.2 to -8.0 ± 11.5 to -14.3 ± 8.4%, respectively, during euglycemia, P = 0.0001). During clamped euglycemia, aliskiren increased FMD; dual therapy exaggerated this effect (5.1 ± 3.3 to 7.5 ± 3.0 to 10.8 ± 3.5%, repeated-measures ANOVA, P = 0.0001). Aliskiren monotherapy caused renal vasodilatation during clamped hyperglycemia only. In contrast, dual therapy augmented renal vasodilatory effects during clamped euglycemia and hyperglycemia. CONCLUSIONS: In patients with uncomplicated type 1 diabetes, aliskiren-based dual RAS blockade is associated with greater arterial compliance, FMD, and renal vasodilatation.
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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| 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) | 0.001 | 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".