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February 8, 2026European Heart Journal0 citations

Predictors of ascending aortic dilation in patients with bicuspid aortic valve

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YHY HeXGX Y GuXZX Zhang

Key Points

  • The study aims to identify predictive factors for ascending aortic dilation in patients with bicuspid aortic valve.
  • Retrospective analysis of 4,196 patients with bicuspid aortic valve from 2023-2024.
  • Exclusion of patients with connective tissue disorders.
  • Assessment of demographics, Sievers classification, aortic stenosis severity, comorbidities, and ascending aortic diameter.
  • Utilization of univariate and multivariate logistic regression for predictor identification.
  • 34% of patients (1,444) exhibited ascending aortic dilation.
  • Univariate analysis identified significant predictors, including age, sex, BAV morphology, aortic stenosis severity, hypertension, and baseline aortic diameter.
  • Multivariate analysis confirmed age and aortic stenosis severity as independent predictors.

Abstract

Abstract Background Bicuspid aortic valve (BAV), the most common congenital cardiac malformation (prevalence 1-2%), is strongly associated with ascending aortic dilation (20-84% incidence), a life-threatening risk factor for aortic dissection. Early identification of predictive factors is critical for risk stratification and clinical management. Methods This retrospective study analyzed 4,196 BAV patients from our hospital (2023–2024). Exclusion criteria included connective tissue disorders. Variables included demographics, Sievers classification, aortic stenosis severity (echocardiography), comorbidities, and ascending aortic diameter. Univariate/multivariate logistic regression identified predictors of dilation (defined as ≥40 mm). Results Of 4,196 patients, 1,444 (34%) had ascending aortic dilation. Univariate analysis linked age (P0.01), sex (P=0.03), BAV morphology (P=0.02), aortic stenosis severity (P0.01), hypertension (P=0.04), and baseline aortic diameter (P0.01) to dilation. Multivariate analysis confirmed age (OR=1.05, 95% CI 1.02–1.08) and aortic stenosis severity (OR=2.34, 95% CI 1.78–3.07) as independent predictors (both P0.01). Discussion: Aging accelerates aortic wall degradation (elastic fiber fragmentation) and reduces structural integrity, while stenosis-induced hemodynamic stress exacerbates dilation. BAV patients inherently exhibit aortic wall abnormalities (e.g., cystic medial necrosis), compounding risk. These mechanisms highlight the synergistic role of age and stenosis in dilation progression. Conclusion Age and aortic stenosis severity independently predict ascending aortic dilation in BAV patients. Elderly patients with severe stenosis warrant intensified imaging surveillance to enable early intervention and mitigate complications.

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Cite This Study

He et al. (2025) studied this question.

synapsesocial.com/papers/698827670fc35cd7a8846218https://doi.org/10.1093/eurheartj/ehaf784.2323
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