Usefulness of two-dimensional speckle tracking echocardiography in assessment of left atrial fibrosis degree and its application in atrial fibrillation.

This study aimed to establish a clinical prediction model for assessing the degree of left atrial fibrosis (LAF) in patients with atrial fibrillation (AF) by combining two-dimensional speckle tracking echocardiography (2D-STE). Additionally, the study sought to evaluate the predictive utility of 2D-STE for left atrial appendage thrombosis (LAAT) and the recurrence of AF after radiofrequency catheter ablation (RFA). A total of 195 patients with AF were included, and late gadolinium enhanced cardiac magnetic resonance was adopted to assess LAF degree. Fibrotic tissue as a percentage of total left atrial wall volume > 20% was defined as severe LAF. Echocardiographic parameters were obtained and analyzed using 2D-STE. The patients were randomly divided into two cohorts (7:3) as the training and testing cohorts. Independent predictors of severe LAF were determined via univariate and multivariate logistic regression, including age, CHADS-VA score, left atrial appendage emptying fraction (LAA-EF), peak atrial longitudinal strain (PALS), left atrial stiffness index (LASI), left atrial strain during contraction phase (LASct) and left atrial strain during conduit phase (LAScd). The nomogram was established with the above variables and the area under the curve of the nomogram in testing cohorts was 0.89 (95% CI, 0.80-0.98). As validated by receiver operating characteristic curves, calibration curves and decision curve analysis, the nomogram model demonstrated promising potential for clinical application. Besides, by univariate and multivariate logistic regression analyses, CHADS-VA score, uric acid, LAA-EF, left atrial appendage peak blood flow emptying velocity (LAA-PEV) and LASct were found to be independent predictors of LAAT, and left atrial appendage length, E/e' and LASct were found to be independent predictors of post-ablation AF recurrence. 2D-STE can be applied to evaluate LAF degree of AF patients and predict LAAT and AF recurrence.