Angiotensin II–Converting Enzyme Inhibition Improves Survival, Ventricular Remodeling, and Myocardial Energetics in Experimental Aortic Regurgitation
Bibliographic record
Abstract
BACKGROUND: Aortic valve regurgitation (AR) is a volume-overload disease causing severe eccentric left ventricular (LV) hypertrophy and eventually heart failure. There is currently no approved drug to treat patients with AR. Many vasodilators including angiotensin-converting enzyme inhibitors have been evaluated in clinical trials, but although some results were promising, others were inconclusive. Overall, no drug has yet been able to improve clinical outcome in AR and the controversy remains. We have previously shown in an animal model that captopril (Cpt) reduced LV hypertrophy and protected LV systolic function, but we had not evaluated the clinical outcome. This protocol was designed to evaluate the effects of a long-term Cpt treatment on survival in the same animal model of severe aortic valve regurgitation. METHODS AND RESULTS: Forty Wistar rats with AR were treated or untreated with Cpt (1 g/L in drinking water) for a period of 7 months to evaluate survival, myocardial remodeling, and function by echocardiography as well as myocardial metabolism by µ positron emission tomography scan. Survival was significantly improved in Cpt-treated animals with a survival benefit visible as soon as after 4 months of treatment. Cpt reduced LV dilatation and LV hypertrophy. It also significantly improved the myocardial metabolic profile by restoring the level of fatty acids metabolic enzymes and use. CONCLUSIONS: In a controlled animal model of pure severe aortic valve regurgitation, Cpt treatment reduced LV remodeling and LV hypertrophy and improved myocardial metabolic profile and survival. These results support the need to reevaluate the role of angiotensin-converting enzyme inhibitors in humans with AR in a large, carefully designed prospective clinical trial.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".