Treatment of Combined Aortic Regurgitation and Systemic Hypertension: Insights From an Animal Model Study
Bibliographic record
Abstract
BACKGROUND: Hypertension (HT) and aortic valve regurgitation (AR) often coexist but the specific impacts of AR + HT on the left ventricle (LV) are still unknown. The best treatment strategy for this combination of diseases is also unclear. The objectives of this study were 1) to evaluate LV function, remodeling and 2) to assess the effects of the angiotensin-converting enzyme (ACE) inhibitor captopril (C) in rats with AR +/- HT in spontaneously hypertensive rats (SHR). METHODS: Animals were grouped as follows: normotensive (NT) Wistar-Kyoto, NT + AR, hypertensive SHR (HT), and HT + AR receiving or not captopril (150 mg/kg/d). Hearts were evaluated in vivo by echocardiography and harvested for tissue analysis after 6 months of evolution. RESULTS: The HT + AR rats had the worst LV hypertrophy (LVH), subendocardial fibrosis, and lowest ejection fraction. Captopril normalized BP in HT and HT + AR, but could not prevent LVH in HT + AR as well as it did in isolated HT. The LV ejection fraction remained below normal in HT + AR + captopril compared to HT alone + captopril. Cardiomyocyte hypertrophy remained in HT + AR + captopril but was normalized in HT + captopril. Subendocardial fibrosis was reduced by captopril in HT + AR. CONCLUSIONS: The AR + HT rats had the most severe myocardial abnormalities. High dose captopril was effective to slow LVH and preserve normal LV ejection fraction in isolated HT or AR, but was less effective when both pathologies were combined. Prohypertrophic stimuli clearly remain active in HT + AR despite ACE inhibition. These results suggest that a very aggressive medical treatment strategy may be required to optimize LV protection when AR and HT co-exist.
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 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".