Medications for specific phenotypes of heart failure with preserved ejection fraction classified by a machine learning-based clustering model

OBJECTIVE: Our previously established machine learning-based clustering model classified heart failure with preserved ejection fraction (HFpEF) into four distinct phenotypes. Given the heterogeneous pathophysiology of HFpEF, specific medications may have favourable effects in specific phenotypes of...

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Detalles Bibliográficos
Autores principales: Sotomi, Yohei, Hikoso, Shungo, Nakatani, Daisaku, Okada, Katsuki, Dohi, Tomoharu, Sunaga, Akihiro, Kida, Hirota, Sato, Taiki, Matsuoka, Yuki, Kitamura, Tetsuhisa, Komukai, Sho, Seo, Masahiro, Yano, Masamichi, Hayashi, Takaharu, Nakagawa, Akito, Nakagawa, Yusuke, Tamaki, Shunsuke, Ohtani, Tomohito, Yasumura, Yoshio, Yamada, Takahisa, Sakata, Yasushi
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BMJ Publishing Group 2023
Materias:
Heart Failure and Cardiomyopathies
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10423528/
https://www.ncbi.nlm.nih.gov/pubmed/36822821
http://dx.doi.org/10.1136/heartjnl-2022-322181

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10423528/
https://www.ncbi.nlm.nih.gov/pubmed/36822821
http://dx.doi.org/10.1136/heartjnl-2022-322181

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