Emerging predictive power of myocardial deformation in chronic kidney disease

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Introduction: Cardiovascular disease is the major cause of morbidity and mortality in patients with advanced chronic kidney disease (CKD). In the last decade a growing number of cardiac biomarkers have been identified as risk factors linked to adverse cardiovascular outcomes in patients with renal failure. Moreover, several cardiac structural abnormalities, identified mainly by echocardiography, were also found in relation to CKD. Echocardiography continuously provides new imaging modalities, which are characterized by increasing ability to identify subtle functional or structural changes of the heart. In the present study we evaluated the prognostic information that can be gained from traditional and novel echocardiographic parameters in combination with selected biomarkers in two groups of patients, predialysis and dialysis. Methods: The study cohort consisted of 50 predialysis and 45 dialysis patients (mean age 60.6±15.8 years) followed-up between September 2006 and January 2013 (76 months, 6.3 years). The association of selected humoral biomarkers (BNP, C-reactive protein, and fibrinogen), and echocardiographic parameters to survival in both groups of patients was assessed. A comprehensive list of quantitative parameters of left-sided chamber size, geometry, systolic and diastolic function, and valvular function were measured from the echocardiogram. Global longitudinal strain (GLS), strain rate (GLSR), circumferential strain (CS) and strain rate (CSR) were assessed from two-dimensional images using speckle tracking based velocity vector imaging. The primary outcome was all-cause mortality. To test the appropriateness of the humoral and echocardiographic parameters for survival analysis, a multivariable logistic regression model was used. The variables with a p value <0.05 were selected for further Cox proportional hazards regression analysis which was used to identify the optimal parameters to predict all-cause mortality. The optimal variables identified in the above model were then entered in a subsequent Kaplan-Meier method. Results: Comparison of survival curves using log-rank test revealed that significant predictors of all-cause mortality were GLS (p=0.008), CSR (p=0.006) and LV EF (p=0.04) in predialysis patients (Figures 1-3) and CRP (p=0.02) and E/Em (p=0.02) in the group of dialysis patients. Conclusion: The results of our study suggest that the predictive power of LV EF was outweighed by deformation indexes, such as GLS and CSR in predialysis patients. In hemodialysis patients the most powerful predictors of survival were C-reactive protein and E/Em.