The utility of combining continuous wavelet transform analysis and high-density voltage map in predicting the long-term outcomes after ablation of persistent atrial fibrillation
Journal of Interventional Cardiac Electrophysiology(2022)
摘要
Background Continuous wavelet transform (CWT) analysis is a frequency analysis to detect areas of stable high-frequent activity (stable pseudo frequency [sPF]) during atrial fibrillation (AF). As previously reported, patients with the highest sPF area in pulmonary veins (PV) showed better short-term outcomes after PV isolation (PVI). This study sought to evaluate the efficacy of CWT analysis in predicting the long-term (2 years) outcomes after PVI. We also combined the left atrial (LA) voltage map with CWT analysis to further predict the outcome. Methods Persistent AF patients ( n = 109, age 65 ± 10) underwent a CWT analysis at PVs and 8 LA sites during AF for pre-PVI analysis. After PVI during AF, CWT analysis was performed again in the LA as post-PVI analysis and was compared with pre-PVI analysis. A sinus voltage map of LA was created after cardioversion. Results Seventy patients had the highest sPF within PVs (PV-dominant group), while 39 patients had the highest sPF outside PVs (LA-dominant group). The global frequency in the LA showed a significant decrease after PVI only in PV-dominant group (6.55 ± 0.27 to 6.43 ± 0.37, P < 0.01). AF-free survival was better in PV-dominant group than LA-dominant group at 2-year follow-up (87.1% vs. 64.3%, P < 0.002). This trend was recognized throughout all degrees of low voltage area in the LA (LA-LVA), and AF-free survival was well predicted by combining CWT analysis and LA-LVA. Conclusions By combining CWT analysis and sinus LA-LVA, the long-term AF-free survival after PVI was well stratified and predicted.
更多查看译文
关键词
Persistent atrial fibrillation, Site of stable highest frequency, Sinus voltage map, Catheter ablation
AI 理解论文
溯源树
样例
![](https://originalfileserver.aminer.cn/sys/aminer/pubs/mrt_preview.jpeg)
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要