Combination Angiotensin Converting Enzyme and Direct Renin Inhibition in Heart Failure following Experimental Myocardial Infarction
Bibliographic record
Abstract
AIMS: Diminishing the activity of the renin-angiotensin system (RAS) plays a pivotal role in the treatment of heart failure. In addition to angiotensin converting enzyme (ACE) inhibitors and angiotensin-receptor blockers, direct renin inhibition has emerged as a potential adjunctive treatment to conventional RAS blockade. We sought to determine the effectiveness of this strategy after myocardial infarction (MI) in the setting of preexisting hypertension, a common premorbid condition in patients with ischemic heart disease. METHODS AND RESULTS: Ten-week-old female heterozygous hypertensive (mRen-2)27 transgenic rats (Ren-2), were randomized to one of five groups (n = 8 per group); sham, MI, MI + aliskiren, MI + lisinopril and MI + combination lisinopril and aliskiren. Cardiac function was assessed by echocardiography and in vivo cardiac catheterization. Untreated MI animals developed heart failure with hypotension, dilation, reduced ejection fraction (EF), and raised left ventricular end-diastolic pressure (LVEDP). Treatment with single agent treatment had only modest effect on cardiac function though combination therapy was associated with significant improvements in EF and LVEDP when compared to untreated MI animals (P < 0.05). Histologic analysis demonstrated increase extracellular matrix deposition and cardiomyocyte hypertrophy in the noninfarct region of all MI groups when compared with sham operated animals (P < 0.05) that was reduced by ACE inhibitor monotherapy and combination treatment but not by aliskiren alone. CONCLUSION: In a hypertensive rat model that underwent experimental MI, EF, and LVEDP, key functional indices of heart failure, were improved by treatment with combination ACE and direct renin inhibition when compared with either agent used alone.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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".