Left Atrial Appendage Mechanical Dispersion Assessed by Speckle-Tracking Echocardiography as a Determinant of Left Atrial Appendage Blood Stasis in Patients With Atrial Fibrillation

Two-dimensional speckle tracking imaging analyses of the correlations between left atrial appendage function and stroke risk in nonvalvular atrial fibrillation patients

Stroke incidence is the most severe complication associated with atrial fibrillation (AF), and the most common site of thrombus formation in AF patients is the left atrial appendage (LAA). This study was developed to use two-dimensional speckle tracking imaging (2D-STI) to explore associations between LAA strain/strain rate and stroke incidence and to evaluate the value of utilizing LAA strain and strain rate values to support the stratification of nonvalvular AF (NVAF) patients based on stroke risk. A total of 486 AF patients who had undergone transesophageal echocardiography to exclude potential intracardiac thrombosis between March 2021 and November 2022 were consecutively enrolled. Patients meeting the inclusion criteria were separated into two groups according to their history of stroke/transient ischemic attack (TIA). LAA strain and strain rate values in these patients were measured via 2D-STI. Multivariable logistic regression analysis was employed to determine independent risk factors for the construction of a combined predictive model. Of the 333 analyzed patients (134 females, aged 65 (56,72) years), 39 (11.71%, 39/333) had a history of stroke at the time of evaluation. Multivariate logistic regression analysis demonstrated that nonparoxysmal AF, CHA2DS2VASc score, LAA thrombus/spontaneous echo contrast (SEC), LAA strain, and strain rate were all predictors of stroke incidence among NVAF patients. The combined predictive model demonstrated excellent discriminative ability, with an AUC of 0.91 (95%CI 0.87-0.95, P < 0.001), and a sensitivity and specificity of 79.49% and 89.46%, respectively. The Hosmer-Lemeshow test confirmed good calibration, yielding a value of 0.98. Comparative decision curve analysis showed that the model provided superior net benefits compared to the CHA2DS2VASc score. Furthermore, the model exhibited improved predictive performance and reclassification for stroke when compared to the CHA2DS2VASc score (AUC 0.91 vs. 0.88, Z = 2.32, P = 0.02), accompanied by a significant increase in the net reclassification index (+ 5.44%, P < 0.001) and integrated discrimination improvement (8.21%, P < 0.001). These data demonstrate that LAA strain and strain rate, as measured via 2D-STI, can offer value when assessing LAA function in AF patients, potentially providing further predictive value to extant clinical risk scoring strategies.

Nomogram to predict recurrence risk factors in patients with non-valvular paroxysmal atrial fibrillation after catheter radiofrequency ablation

BACKGROUND

Radiofrequency catheter ablation (RFCA) is an effective method for controlling the heart rate of paroxysmal atrial fibrillation (PAF). However, recurrence is trouble under the RFCA. To gain a deeper understanding of the risk factors for recurrence in patients, we created a nomogram model to provide clinicians with treatment recommendations.

METHODS

A total of two hundred thirty-three patients with PAF treated with RFCA at Guizhou Medical University Hospital between January 2021 and December 2022 were consecutively included in this study, and after 1 year of follow-up coverage, 166 patients met the nadir inclusion criteria. Patients with AF were divided into an AF recurrence group and a non-recurrence group. The nomogram was constructed using univariate and multivariate logistic regression analyses. By calculating the area under the curve, we analyzed the predictive ability of the risk scores (AUC). In addition, the performance of the nomogram in terms of calibration, discrimination, and clinical utility was evaluated.

RESULTS

At the 12-month follow-up, 48 patients (28.92%) experienced a recurrence of AF after RFCA, while 118 patients (71.08%) maintained a sinus rhythm. In addition to age, sex, and TRV, LAD, and TTPG were independent predictors of recurrence of RFCA. The c-index of the nomogram predicted AF recurrence with an accuracy of .723, showing good decision curves and a calibrated nomogram, as determined by internal validation using a bootstrap sample size of 1000.

CONCLUSION

We created a nomogram based on multifactorial logistic regression analysis to estimate the probability of recurrence in patients with atrial fibrillation 1 year after catheter ablation. This plot can be utilized by clinicians to predict the likelihood of recurrence.