Abstract TH152: Molecular Pathways of Cardiac Fibrosis in Hypertension: A Systematic Review of Mechanisms and Therapeutic Implications
Bibliographic record
Abstract
Introduction: Heart fibrosis caused by high blood pressure is the main reason behind heart failure and stiffness. Excessive activation of RAAS, TGF-β, and ongoing inflammation are examples of molecular changes related to the development of myocardial fibrosis in high blood pressure conditions. The significance of these pathways and their possible use as drug targets has not been investigated broadly. Our goal was to assemble information about the mechanisms of cardiac fibrosis in hypertension and to determine how treatment might affect them. Hypothesis: Using combination therapy that targets RAAS along with TGF-β will lead to a greater decrease in myocardial fibrosis and help improve diastolic function than standard RAAS blockade alone in patients with hypertension and elevated TGF-β, galectin-3 and procollagen type I C-terminal propeptide levels over 12 months. Methods: Following PRISMA guidelines, we reviewed studies looking at molecular indicators or processes of myocardial fibrosis in patients with hypertension. Studies were included: 3 randomized controlled trials and 12 observational studies. These studies examined markers in the blood and heart, how the heart tissue appeared on imaging, and whether fibrosis affected the outcomes. The ability to identify errors was reviewed through the Cochrane Risk of Bias for randomized controlled trials and the Newcastle-Ottawa for observational studies. Results: Patients with hypertension tend to have higher levels of profibrotic mediators such as angiotensin II, aldosterone, TGF-β, and inflammatory cytokines. Observational studies suggest a clear link between high levels of circulating fibrosis markers and both the increased thickness of the left ventricle and reduced heart-filling ability in hypertensive people. In small RCTs, RAAS blockade with ACE inhibitors, ARBs, or mineralocorticoid receptor antagonists helped lower fibrosis biomarkers. It could even restore some of the fibrotic changes seen in the heart. The chance of bias was very low in RCTs, compared to observational studies. Conclusions: Several pathways working together contribute to myocardial fibrosis in hypertension, and changing their roles can help prevent heart damage. It emphasizes that besides reducing blood pressure, using approaches to prevent fibrosis may bring more cardiovascular benefits. More studies are needed to find and develop customized antifibrotic therapies for hypertensive heart disease.
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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 | 0.015 | 0.037 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.008 | 0.010 |
| Bibliometrics | 0.012 | 0.012 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 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".