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SQUMJ-Sultan Qaboos University Medical Journal. 2013; 13 (4): 552-559
in English | IMEMR | ID: emr-159038

ABSTRACT

The 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]. Their influence on heart failure [HF] outcomes at a one-year follow-up, not clarified in previous studies, was also examined. 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. 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 identified as independent predictors for cardiac events. Significant 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 significantly correlated to age, ejection fraction and velocity. Advanced STE is a promising technique which accelerates the clinical application of the quantification of myocardial function and synchrony. STE parameters and NT-proBNP have the ability to identify patients at higher risk of death and hospitalisation


Subject(s)
Humans , Male , Female , Echocardiography , Natriuretic Peptide, Brain/blood , Natriuretic Peptide, Brain , Multivariate Analysis , Severity of Illness Index , Predictive Value of Tests , Prospective Studies , Biomarkers , Chi-Square Distribution
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