Rathika Krishnasamy1, Nicole M Isbel1, Carmel M Hawley1, Elaine M Pascoe2, Rodel Leano3, Brian A Haluska3, Tony Stanton3. 1. Department of Renal Medicine, University of Queensland at Princess Alexandra Hospital, Brisbane, Queensland, Australia. 2. School of Medicine, University of Queensland, Brisbane, Queensland, Australia. 3. Cardiovascular Imaging Research Centre, School of Medicine, University of Queensland at Princess Alexandra Hospital, Brisbane, Queensland, Australia.
Abstract
BACKGROUND: Left ventricular (LV) systolic dysfunction is an important predictor of cardiovascular death. Global longitudinal strain (GLS) is a widely available echocardiographic technique proven to be more sensitive than conventional ejection fraction (EF) in detecting subtle changes in LV function. However, the prognostic value of GLS in patients with chronic kidney disease (CKD) is unknown. METHODS: We studied 447 patients from a single center who were stratified according to estimated glomerular filtration rate (eGFR). GLS was calculated using two-dimensional speckle tracking and EF was measured using Simpson's biplane. Cox proportional hazard model was used to identify independent predictors of survival and measures of discrimination and reclassification were used to assess the predictive value of GLS. Multivariable regression models were used to evaluate clinical and laboratory factors associated with GLS. RESULTS: The mean EF was 58 ± 11% and GLS was -16.6 ± 4.2%. eGFR correlated negatively with GLS (r = -0.14, P = 0.004). Factors that were independently associated with GLS include gender, previous myocardial infarction, eGFR and phosphate (R(2) = 0.16, P < 0.001). Sixty-four patients died in a follow-up of 5.2 ± 1.4 years. GLS remained a significant predictor of all-cause mortality [hazard ratio (HR) 1.08, 95% confidence interval (CI) 1.01-1.15] following adjustment for age, diabetes mellitus, hypertension, eGFR and left ventricular mass index (LVMI). The strength of association between demographic data, eGFR, LVMI and mortality increased following addition of GLS [c-statistic 0.68 (95% CI 0.61-0.74) to 0.71 (95% CI 0.64-0.77), P = 0.04]. Addition of GLS also demonstrated a 21% net reclassification improvement in risk prediction for all-cause mortality over clinical factors. CONCLUSIONS: GLS is an important predictor of all-cause mortality in CKD patients. Traditional and non-traditional risk factors such as phosphate are important determinants of GLS. Strain assessment in CKD patients may provide greater cardiovascular risk stratification.
BACKGROUND:Left ventricular (LV) systolic dysfunction is an important predictor of cardiovascular death. Global longitudinal strain (GLS) is a widely available echocardiographic technique proven to be more sensitive than conventional ejection fraction (EF) in detecting subtle changes in LV function. However, the prognostic value of GLS in patients with chronic kidney disease (CKD) is unknown. METHODS: We studied 447 patients from a single center who were stratified according to estimated glomerular filtration rate (eGFR). GLS was calculated using two-dimensional speckle tracking and EF was measured using Simpson's biplane. Cox proportional hazard model was used to identify independent predictors of survival and measures of discrimination and reclassification were used to assess the predictive value of GLS. Multivariable regression models were used to evaluate clinical and laboratory factors associated with GLS. RESULTS: The mean EF was 58 ± 11% and GLS was -16.6 ± 4.2%. eGFR correlated negatively with GLS (r = -0.14, P = 0.004). Factors that were independently associated with GLS include gender, previous myocardial infarction, eGFR and phosphate (R(2) = 0.16, P < 0.001). Sixty-four patients died in a follow-up of 5.2 ± 1.4 years. GLS remained a significant predictor of all-cause mortality [hazard ratio (HR) 1.08, 95% confidence interval (CI) 1.01-1.15] following adjustment for age, diabetes mellitus, hypertension, eGFR and left ventricular mass index (LVMI). The strength of association between demographic data, eGFR, LVMI and mortality increased following addition of GLS [c-statistic 0.68 (95% CI 0.61-0.74) to 0.71 (95% CI 0.64-0.77), P = 0.04]. Addition of GLS also demonstrated a 21% net reclassification improvement in risk prediction for all-cause mortality over clinical factors. CONCLUSIONS: GLS is an important predictor of all-cause mortality in CKDpatients. Traditional and non-traditional risk factors such as phosphate are important determinants of GLS. Strain assessment in CKDpatients may provide greater cardiovascular risk stratification.
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