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Updated: Sep 11, 2025

Lumped-Parameter and Finite Element Modeling of Heart Failure with Preserved Ejection Fraction
Published on: February 13, 2021
Mechanical dispersion predicts survival of dialysis-dependent patients with preserved left ventricular ejection
Milica Scepanovic1, Ivan Stankovic2,3, Tamara Jemcov4,5
1Department of Cardiology, Clinical Hospital Center Zemun, Vukova 9, Belgrade, 11080, Serbia.
Abstract:
Cardiovascular disease is a leading cause of mortality in chronic kidney disease patients undergoing renal replacement therapy (RRT). Echocardiographic risk assessment, especially in patients with preserved left ventricular ejection fraction (LVEF), may help identifying at-risk individuals. This study evaluates the prognostic significance of left ventricular (LV) mass global longitudinal strain (GLS) and mechanical dispersion in RRT patients with preserved LVEF. We prospectively followed 78 RRT patients with LVEF ≥ 50% over 55 ± 6 months to assess all-cause mortality. LV mass was determined using linear measurements and indexed to body surface area to obtain LV mass index (LVMI). GLS was calculated as the average of 18 segmental peak systolic strain values while mechanical dispersion was calculated from time intervals measured from the ECG R-wave to peak longitudinal strain across 18 LV segments. LV hypertrophy was observed in 58% of patients. Over a median follow-up of 55 ± 6 months, 29 patients (37%) died. Univariate Cox regression analysis identified age, diabetes mellitus, LVMI, GLS, and mechanical dispersion as predictors of all-cause mortality. Multivariate analysis confirmed that age [hazard ratio (HR) 1.04, 95% confidence interval (CI) 1.01-1.07, p = 0.014], LVMI (HR 1.02, 95% CI 1.01-1.03, p = 0.001), GLS (HR 0.77, 95%CI 0.66-0.88, p = 0.014) and mechanical dispersion (HR 2.16, 95% CI 1.03-4.52, p = 0.042) were independent mortality predictors. In dialysis-dependent patients with preserved LVEF, increased mechanical dispersion is associated with worse survival. This parameter, when combined with LVMI and GLS, could serve as an additional tool for risk stratification in this vulnerable patient population.
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