Phenotypic clustering of atrial fibrillation patients using latent class analysis and its potential utility for ablation strategy: insights from the DIRECT-Extend and EARNEST-PVI studies
EHJ - Open

Abstract
AF is a heterogeneous syndrome. We aimed to assess whether latent class analysis (LCA) can identify phenotypes that stratify prognosis and predict differential responses to catheter ablation strategies.
We first developed an LCA-based phenotyping model using the DIRECT-Extend registry (
LCA identified distinct AF phenotypes associated with prognoses. These phenotypes may also provide insights into heterogeneity in response to ablation strategies. This phenotyping approach may support risk stratification and individualized AF management.
Contributors

Shun Sasaki
Author

Yuki Matsuoka
Author

Daisuke Sakamoto
Author

Hideaki Hasegawa
Author

Tomoharu Dohi
Author

Hirota Kida
Author

Tetsuhisa Kitamura
Author

Katsuki Okada
Author

Daisaku Nakatani
Author

Hidetaka Kioka
Author

Masaharu Masuda
Author

Tetsuya Watanabe
Author

Yasuo Okumura
Author

Yoshiharu Higuchi
Author

Koichi Inoue
Author

Shungo Hikoso
Author

Yasushi Sakata
Author

Emmanouil Charitakis
Author
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