Combining computed tomography features of left atrial epicardial and pericoronary adipose tissue with the triglyceride-glucose index to predict the recurrence of atrial fibrillation after radiofrequency catheter ablation: a machine learning study
The SVM model that integrated the TyG index and quantitative CT imaging variables demonstrated good predictive ability for post-RFCA recurrence in patients with AF. Furthermore, the TyG index appeared capable of predicting recurrence independently of T2DM status.
Authors
- Aiyun Sun
- Wensu Chen (ORCID: https://orcid.org/0000-0001-9933-8156)
- Zishuo Wang (ORCID: https://orcid.org/0000-0002-1122-4769)
- Yaoyu Zhang (ORCID: https://orcid.org/0009-0007-4275-3026)
- Chengzong Li (ORCID: https://orcid.org/0000-0003-3360-1980)
- Xiaoqiang Li (ORCID: https://orcid.org/0000-0001-5279-9158)
- Siyi Wang (ORCID: https://orcid.org/0000-0002-3754-2861)
- Chunfeng Hu (ORCID: https://orcid.org/0000-0001-6804-7401)
- Lixiang Xie
Institutions
- Xuzhou Medical College (CN)
- United Imaging Healthcare (China) (CN)
Publication Details
- Journal
- Quantitative Imaging in Medicine and Surgery
- Published
- 2024-12-01
- DOI
- https://doi.org/10.21037/qims-24-1393
- Citations
- 2
- Primary Topic
- Cardiovascular Disease and Adiposity
- Type
- article
- Field-Weighted Citation Impact
- 0.80