Left Ventricular 3-Dimensional Global Longitudinal Strain Predicts All-Cause Mortality in Patients With Heart

Shuangshuang Zhu1,2,3, Chun Wu1,2,3, Yiwei Zhang1,2,3

  • 1Department of Ultrasound Medicine Union Hospital, Tongji Medical College, Huazhong University of Science and Technology Wuhan China.

Insights

Three-dimensional left ventricular global longitudinal strain (3D-LVGLS) is a superior predictor of mortality in heart transplant recipients compared to 2D-LVGLS. This finding aids in better risk stratification for these patients.

Area of Science:

  • Cardiology
  • Transplant Medicine
  • Echocardiography

Background:

  • The prognostic significance of 3D-left ventricular global longitudinal strain (LVGLS) in heart transplant (HT) recipients is not well-established.
  • Current prognostic models may not fully capture the risks associated with HT.

Purpose of the Study:

  • To compare the prognostic value of 3D-LVGLS against 2D-LVGLS in predicting outcomes in HT recipients.
  • To determine if 3D-LVGLS offers superior risk stratification capabilities.

Main Methods:

  • Retrospective analysis of adult HT recipients undergoing comprehensive 2D and 3D echocardiography.
  • Feasibility of 3D-LVGLS measurements assessed in 342 patients (86% success rate).
  • All-cause mortality was the primary endpoint, analyzed using Cox regression and C-statistics.

Main Results:

  • 3D-LVGLS demonstrated a significantly higher area under the curve (0.77 vs. 0.67, P=0.012) for predicting mortality compared to 2D-LVGLS.
  • Lower 3D-LVGLS values correlated with worse patient outcomes (P<0.001).
  • A multivariable model incorporating 3D-LVGLS showed improved predictive performance (C-statistic=0.814) versus 2D-LVGLS (C-statistic=0.772).

Conclusions:

  • 3D-LVGLS is a potent predictor of all-cause mortality in heart transplant recipients.
  • 3D-LVGLS provides greater prognostic value than 2D-LVGLS for risk stratification.
  • Evaluating 3D-LVGLS holds significant potential for improving patient management in HT recipients.
Abstract