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
Xiaole Li, Zishuo Wang, Siyi Wang, Wensu Chen, Chengzong Li, Yinyang Zhang, Aiyun Sun, Lixiang Xie, Chunfeng Hu · 2024
Read 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 by Xiaole Li, Zishuo Wang, Siyi Wang, Wensu Chen, Chengzong Li, Yinyang Zhang, Aiyun Sun, Lixiang Xie, Chunfeng Hu (2024) in the Tower of Babel, a free online library of public-domain works preserved in clean, searchable text. No sign-up. The full text is served as a plain-text file at a predictable URL, where text is present: https://antarctic-labs.com/tower-of-babel/pmc-11651957.txt.
Description
Xiaole Li and eight colleagues build a machine learning predictor for atrial fibrillation coming back after catheter ablation, the keyhole procedure that treats the rhythm disorder. Among 325 patients treated a first time, seventy-nine saw their fibrillation return. The team paired a blood-based insulin resistance index with CT measures of fat around the atrium and the coronary arteries.
Four factors on their own predicted recurrence: the volume and density of fat on the atrium, fat inflammation around one coronary branch, and the metabolic index. A support vector machine built on them predicted recurrence well, whatever the diabetes status. The model offers a practical way to flag patients who need closer follow-up after ablation.
Catalog record
| CREATOR | Xiaole Li, Zishuo Wang, Siyi Wang, Wensu Chen, Chengzong Li, Yinyang Zhang, Aiyun Sun, Lixiang Xie, Chunfeng Hu |
|---|---|
| YEAR | 2024 |
| COLLECTION | PAPERS |
| FORMAT | TXT |
| FILE SIZE | 50 KB |
| VERSION | 1.0 |
| LICENSE | CC BY 4.0 |
| RIGHTS | CC BY |
| SOURCE | Europe PMC |