Prediction of Ventricular Arrhythmias With Left Ventricular Mechanical Dispersion: A Systematic Review and Meta-Analysis.

OBJECTIVES

The aim of this study was to assess the association between left ventricular mechanical dispersion (LVMD) and the incidence of ventricular arrhythmias (VAs).

BACKGROUND

Recent, mainly single-center, studies have demonstrated that LVMD assessed using speckle tracking might be a powerful marker in risk stratification for VA. A systematic review and meta-analysis provides a means of understanding the prognostic value of this parameter, relative to other parameters, the most appropriate cutoff for designating risk.

METHODS

A systemic review of studies reporting the predictive value of LVMD for VA was undertaken from a search of MEDLINE and Embase. VA events were defined as sudden cardiac death, cardiac arrest, documented ventricular tachyarrhythmia, and appropriate implantable cardioverter-defibrillator (ICD) therapy. Hazard ratios were extracted from univariate and multivariate models reporting on the association of LVMD and VA and described as pooled estimates with 95% confidence intervals. In a meta-analysis, the predictive value of LVMD was compared with that of left ventricular ejection fraction and global longitudinal strain.

RESULTS

Among 3,198 patients in 12 published studies, 387 (12%) had VA events over follow-up ranging from 17 to 70 months. Patients with VAs had greater LVMD than those without (weighted mean difference -20.3 ms; 95% confidence interval: -27.3 to -13.2; p < 0.01). Each 10 ms increment of LVMD was significantly and independently associated with VA events (hazard ratio: 1.19; 95% confidence interval: 1.09 to 1.29; p < 0.01). The predictive value of LVMD was superior to that of left ventricular ejection fraction or global longitudinal strain.

CONCLUSIONS

LVMD assessed using speckle tracking provides important predictive value for VA in patients with a number of cardiac diseases and appears to have superior predictive value over left ventricular ejection fraction and global longitudinal strain for risk stratification.