Prediction of the impact of anxiety on atrial fibrillation recurrence after radiofrequency catheter ablation based on heart rate variability - Ren, Yufei; Zhang, Hua; Tian, Yingji (Frontiers in Surgery, 2025)
BackgroundRadiofrequency catheter ablation (RFCA) can significantly improve the prognosis of patients with atrial fibrillation (AF); however, the postoperative recurrence rate remains high. Therefore, identifying accurate predictors of recurrence after RFCA holds important clinical value.MethodsThis retrospective study included 180 patients with AF who underwent RFCA. Patients were grouped by one-year recurrence status. Univariate analysis was conducted to compare demographic and clinical characteristics between the two groups. Cox proportional hazards models and Kaplan–Meier survival curves were used to assess the impact of heart rate variability (HRV), anxiety, and their interaction on recurrence. Predictive performance was evaluated with receiver operating characteristic (ROC) curves. Stratified analyses were performed to explore whether the effect of anxiety on recurrence varied by HRV levels.ResultsCompared with the non-recurrence group, the recurrence group had higher prevalence of persistent AF and heart failure, longer AF duration, and more severe left atrial structural burden (i.e., higher EFT, LAD, and LAVI values). Multivariate Cox analysis identified that both HRV and anxiety were independent risk factors for recurrence, and their interaction term also had significant predictive value (HR > 1, P < 0.05). Kaplan–Meier analysis indicated that patients with low HRV and high anxiety had the lowest recurrence-free survival rate. ROC curve analysis revealed that the combined HRV-anxiety interaction model yielded an AUC of 0.745, indicating a certain predictive advantage over individual indicators. Stratified analysis further confirmed that the recurrence risk associated with high anxiety was more pronounced in the low HRV group.ConclusionHRV and anxiety were identified as independent predictors of AF recurrence following RFCA, with a significant synergistic interaction observed between the two. Their combined assessment may enhance the accuracy of recurrence risk prediction and provide a foundation for the development of individualized intervention strategies.