Valvular Heart Disease Associations with Cardiac Biomarkers Using AI-guided Echocardiography: the RURAL Cohort Study

利用人工智能引导的超声心动图分析瓣膜性心脏病与心脏生物标志物的关联:农村队列研究

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Abstract

BACKGROUND: Few studies have evaluated the prevalence or severity of mitral valve prolapse (MVP) and other valvular heart disease (VHD) in the rural US South, where strategies for early detection are crucial for risk stratification and prevention. OBJECTIVES: We assessed the prevalence of MVP and other VHD in a rural US South cohort and examined associations with cardiovascular disease (CVD) risk. We also evaluated relationships between MVP severity, high-sensitivity cardiac troponin T (hsTnT), and N-terminal pro-B-type natriuretic peptide (NTproBNP). METHODS: We conducted a cross-sectional analysis from the Risk Underlying Rural Areas Longitudinal (RURAL) study. Logistic regression assessed associations between participant characteristics and MVP, other VHD, or both. Weighted models assessed odds for MVP and other VHD by 10-year CVD risk categories using the Predicting Risk of CVD Events (PREVENT) score. Among a subset, we evaluated associations between MVP severity and cardiac biomarkers. RESULTS: Among 2,621 participants (68.7% women), MVP and other VHD were present in 1.9% and 11.2%, respectively. Compared to the low PREVENT risk group, odds of MVP were lower and odds of VHD were higher among borderline and intermediate/high groups. HsTnT was lower in MVP vs. non-MVP (0.64, 95% CI 0.58-0.71), without difference by severity of MVP. NTproBNP was higher in participants with severe MVP than non-MVP (2.05, 95% CI 1.49-2.83). CONCLUSIONS: MVP prevalence aligned with population-based epidemiologic studies. PREVENT risk category may differentiate individuals at higher risk for MVP and for other VHD. Future studies are needed to evaluate relationships between MVP/VHD status and clinical events.

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