ArticleThe international journal of cardiovascular imaging2023
Mechanical dispersion is a superior echocardiographic feature to predict exercise capacity in preclinical and overt heart failure with preserved ejection fraction.
Article in The international journal of cardiovascular imaging, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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Who cites it
3 citing papers in PubMed, 8 citations in OpenAlex.
- Peak strain dispersion as a nonlinear mediator in HFpEF: Unraveling subtype-specific pathways via SHAP-augmented ensemble modeling.PLoS computational biology · 2026Article
- Advancing the Diagnosis and Management of Heart Failure with Preserved Ejection Fraction: A Call for Exercise Hemodynamics.Arquivos brasileiros de cardiologia · 2024Article
- Left ventricular and atrial myocardial strain in heart failure with preserved ejection fraction: the evidence so far and prospects for phenotyping strategy.Cardiovascular ultrasound · 2024Review
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Authors and funding
10 authors at 3 institutions in 1 country.
Funding
Abstract
backgroundHeart Failure with Preserved Ejection Fraction (HFpEF) is a syndrome characterized by different degrees of exercise intolerance, which leads to poor quality of life and prognosis. Recently, the European score (HFA-PEFF) was proposed to standardize the diagnosis of HFpEF. Even though Global Longitudinal Strain (GLS) is a component of HFA-PEFF, the role of other strain parameters, such as Mechanical Dispersion (MD), has yet to be studied. In this study, we aimed to compare MD and other features from the HFA-PEFF according to their association with exercise capacity in an outpatient population of subjects at risk or suspected HFpEF.
methodsThis is a single-center cross-sectional study performed in an outpatient population of 144 subjects with a median age of 57 years, 58% females, referred to the Echocardiography and Cardiopulmonary Exercise Test to investigate HFpEF.
resultsMD had a higher correlation to Peak VO2 (r=-0.43) when compared to GLS (r=-0.26), MD presented a significant correlation to Ventilatory Anaerobic Threshold (VAT) (r=-0.20; p = 0.04), while GLS showed no correlation (r=-0.14; p = 0.15). Neither MD nor GLS showed a correlation with the time to recover VO2 after exercise (T1/2). In Receiver Operator Characteristic (ROC) analysis, MD presented superior performance to GLS to predict Peak VO2 (AUC: 0.77 vs. 0.62), VAT (AUC: 0.61 vs. 0.57), and T1/2 (AUC: 0.64 vs. 0.57). Adding MD to HFA-PEFF improved the model performance (AUC from 0.77 to 0.81).
conclusionMD presented a higher association with Peak VO2 when compared to GLS and most features from the HFA-PEFF. Adding MD to the HFA-PEFF improved the model performance.
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