Structural Remodeling in Rheumatic Heart Disease: Influence of Age and Gender in an Egyptian Cohort
Bibliographic record
Abstract
Rheumatic heart disease (RHD) remains a significant cause of cardiovascular morbidity globally, with notable variability in disease progression linked to patient demographics. This study investigated age- and gender-related differences in structural and extracellular matrix (ECM) remodeling in valve tissues from an Egyptian cohort of 88 RHD patients (37 males and 51 females; mean age 38 years at operation), selected for histological analysis from a total of 601 valve replacement and 344 valve repair procedures. The examined cases included individuals who underwent aortic valve replacement (n=34), mitral valve replacement or repair (n=41), or double valve replacements (aortic and mitral valves) (n=13). Biopsies were examined histologically using Hematoxylin and eosin (n=88), Picrosirius Red (n=88), Elastin Van Gieson (n=38), and Alcian Blue (n=38), with quantitative analysis performed via Fiji software. Our results revealed a significant increase in collagen deposition in female valve tissue compared to male tissue, indicating extensive fibrotic remodeling in females. Elastin fibers were fragmented and dispersed throughout the entire leaflet in both genders equally. Additionally, Alcian Blue staining revealed glycosaminoglycans accumulation in both male and female RHD patients, with a higher index in females, further supporting enhanced ECM remodeling. Age-related analysis demonstrated a general increase in fibrotic content with advancing age across both genders. These findings suggest that both age and gender influence ECM dynamics and structural remodeling in RHD-affected valves, with females exhibiting more pronounced fibrotic and ECM changes. Understanding these biological differences is critical for developing gender-specific and age-adapted approaches to the clinical management of RHD.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| 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 | 0.000 | 0.000 |
| 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".