Benefits of long-term β-blockade in experimental chronic aortic regurgitation
Bibliographic record
Abstract
The objective of this study was to assess the long-term effects of beta-blockade on survival and left ventricular (LV) remodeling in rats with aortic valve regurgitation (AR). The pharmacological management of chronic AR remains controversial. No drug has been definitively proven to delay the need for valve replacement or to affect morbidity and/or mortality. Our group has reported that the adrenergic system is activated in an animal model of AR and that adrenergic blockade may help maintain normal LV function. The effects of prolonged treatment with a beta-blocker are unknown. Forty Wistar rats with severe AR were divided into 2 groups of 20 animals each and treated with metoprolol (Met, 25 mg.kg(-1).day(-1)) or left untreated for 1 yr. LV remodeling was evaluated by echocardiography. Survival was assessed by Kaplan-Meir curves. Hearts were harvested for tissue analysis. All Met-treated animals were alive after 6 mo vs. 70% of untreated animals. After 1 yr, 60% of Met-treated animals were alive vs. 35% of untreated animals (P = 0.028). All deaths, except one, were sudden. There were no differences in LV ejection fraction (all >50%) or LV dimensions. LV mass tended to be lower in the Met-treated group. There was less subendocardial fibrosis in this group, as well as lower LV filling pressures (LV end-diastolic pressure). beta-Adrenergic receptor ratio (beta(1)/beta(2)) was improved. One year of treatment with Met was well tolerated. Met improved 1-yr survival, minimized LV hypertrophy, improved LV filling pressures, decreased LV subendocardial fibrosis, and helped restore the beta-adrenergic receptor ratio.
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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 | 0.000 | 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 | 0.000 | 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".