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A Simplified, Tier-Based Method for Clinical Evaluation of Diastolic Function
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PRE
AI
DOI：10.1093/ehjci/jeag123.png)
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Abstract
En 中文
Assessment of left ventricular diastolic function is inherently complex, yet it must be sufficiently simplified for consistent application in clinical practice. Interpretation is challenged by overlapping terminology, load dependence of hemodynamic variables, and the need to integrate multiple echocardiographic parameters that are often discordant. This review presents a simplified, clinically oriented approach to applying contemporary imaging guidelines for diastolic function assessment, with a focus on the 2025 American Society of Echocardiography recommendations. A probabilistic diagnostic framework is emphasized, integrating clinical context, echocardiographic findings, and advanced imaging when appropriate. There are emerging artificial intelligence–based approaches that conceptualize diastolic dysfunction as a latent phenotype, integrating multidimensional imaging and clinical data to improve diagnostic and prognostic assessment beyond traditional stepwise algorithms. The pragmatic approach described in the current review aims to enhance clinical relevance, improve interpretive confidence, and facilitate consistent application of diastolic function assessment in routine practice.
Keywords:
diastolic function
echocardiography
clinical assessment
artificial intelligence
probabilistic framework
Journal
E
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177
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