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Updated: Aug 4, 2025

Echocardiographic Approaches and Protocols for Comprehensive Phenotypic Characterization of Valvular Heart Disease in Mice
Published on: February 14, 2017
Mechanical dispersion is a superior echocardiographic feature to predict exercise capacity in preclinical and overt
Renato A Hortegal1, Carlos Hossri2, Luiz Giolo3
1Instituto Dante Pazzanese de Cardiologia, Av. Dr. Dante Pazzanese, 500, São Paulo, SP, Brazil. renato.hortegal@dantepazzanese.org.br.
Background:
Heart 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.
Methods:
This 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.
Results:
MD 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).
Conclusion:
MD 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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