Systolic Function and Intraventricular Mechanical Dyssynchrony Assessed by Advanced Speckle Tracking Imaging with N-terminal Prohormone of Brain Natriuretic Peptide for Outcome Prediction in Chronic Heart Failure Patients
Journal Title: Sultan Qaboos University Medical Journal - Year 2013, Vol 13, Issue 4
Abstract
Objectives: Te aim of this study was to assess longitudinal systolic function and mechanical synchrony parameters derived from advanced speckle tracking echocardiography (STE) and to determine their correlation with N-terminal prohormone of brain natriuretic peptide (NT-proBNP). Teir influence on heart failure (HF) outcomes at a one-year follow-up, not clarifed in previous studies, was also examined. Methods: Advanced STE was performed from August 2009 to January 2012 in 103 chronic HF patients at the University Kebangsaan Malaysia Medical Center to assess their longitudinal systolic function and synchrony parameters; NT-proBNP blood measurement was taken at the same time. Results: Longitudinal cardiac velocity; strain; strain rate; displacement; intraventricular mechanical dyssynchrony based on the standard deviation (SD) of time to peak systolic strain rate (Tsr-SD); displacement, and antero-septal to posterior (AS-P) delay were associated with cardiac events. In multivariate analysis, NT-proBNP and AS-P delay were identifed as independent predictors for cardiac events. Signifcant correlations were found between NT-proBNP and longitudinal velocity; displacement; strain; strain rate, and ejection fraction. Log NT-proBNP levels correlated moderately with the SD of time to peak displacement and to peak strain, and there was a small correlation with maximal differences and SD of time to peak velocity. A multiple linear analysis revealed that NT-proBNP levels signifcantly correlated to age, ejection fraction and velocity. Conclusion: Advanced STE is a promising technique which accelerates the clinical application of the quantifcation of myocardial function and synchrony. STE parameters and NT-proBNP have the ability to identify patients at higher risk of death and hospitalisation.
Authors and Affiliations
Faida A. Obaid| Medical Center, Universiti Kebangsaan Malaysia, Bangi, Selangor, Malaysia, Oteh Maskon| Hospital Universiti Kebangsaan Malaysia (HUKM), Kuala Lumpur, Malaysia, Fadillah Abdolwahid| Medical Center, Universiti Kebangsaan Malaysia, Bangi, Selangor, Malaysia
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