Early Change In Left Atrial And Left Ventricular Strain Predicts Sinus Rhythm Maintenance After Cardioversion

Abstract Background Atrial fibrillation (AF) impairs mechanical function of the heart, especially atria and restoration of sinus rhythm (SR) leads to improvement of mechanics. The predicting role of changes in strain parameters for AF recurrence is not established yet. Purpose To analyse changes in left atrial (LA) and left ventricular (LV) mechanical function after conversion to SR and their prognostic values for AF recurrence during 24 months follow-up. Methods Prospective study involved 59 patients after successful electrical cardioversion (EC) because of nonvalvular AF (mean age 65±4 years, 47% female). Speckle tracking analysis (STE) was applied to calculate longitudinal strain of LV and LA before EC and within 24 hours after restoration of SR and additionally total left heart strain (TS) defined as a sum of absolute peak LV and LA strain. We calculated change in strain between AF and SR analyses expressed as delta (Δ). During follow-up we noticed AF recurrence in 42 (71%) patients, most of them (93%) during 1st year after EC. Median time of AF recurrence was 3 months. Results We noticed significant immediate post-EC improvement in peak LA longitudinal strain (PALS) and LV global longitudinal strain (LVGLS) (table). Unlike CHA2DS2-VASc score, strain parameters were predictors of AF recurrence. Every 1% increment in ΔLVGLS was related with 13% increase in AF recurrence risk (p=0.02) and every 1% increment in ΔPALS and ΔTS were related with 9% decrease in AF recurrence risk (p=0.007 and p=0.0014, respectively). Multivariate analysis revealed ΔTS as a strongest predictor with 9% decrease in AF risk per every 1% increment. The criterion of ΔTS ≤7.5% allows to predict AF recurrence with 81% sensitivity and 63% specificity. Conclusions Speckle tracking measurements are able to detect early mechanical changes in LA even within 24 hours of SR and these absolute changes in LVGLS as well as PALS can predict AF recurrence, with optimal stratification by novel parameter - TS. Funding Acknowledgement Type of funding source: None