Distinct Subtypes of Hepatorenal Syndrome and Associated Outcomes as Identified by Machine Learning Consensus Clustering.

Tangpanithandee, Supawit; Thongprayoon, Charat; Krisanapan, Pajaree; Mao, Michael A; Kaewput, Wisit; Pattharanitima, Pattharawin; Boonpheng, Boonphiphop; Cheungpasitporn, Wisit

Tangpanithandee, Supawit; Thongprayoon, Charat; Krisanapan, Pajaree; Mao, Michael A; Kaewput, Wisit; Pattharanitima, Pattharawin; Boonpheng, Boonphiphop; Cheungpasitporn, Wisit.

Afiliação

Tangpanithandee S; Division of Nephrology and Hypertension, Department of Medicine, Mayo Clinic, Rochester, MN 55905, USA.
Thongprayoon C; Chakri Naruebodindra Medical Institute, Faculty of Medicine Ramathibodi Hospital, Mahidol University, Samut Prakan 10540, Thailand.
Krisanapan P; Division of Nephrology and Hypertension, Department of Medicine, Mayo Clinic, Rochester, MN 55905, USA.
Mao MA; Division of Nephrology and Hypertension, Department of Medicine, Mayo Clinic, Rochester, MN 55905, USA.
Kaewput W; Division of Nephrology, Department of Internal Medicine, Faculty of Medicine Thammasat University, Pathum Thani 12120, Thailand.
Pattharanitima P; Division of Nephrology, Department of Internal Medicine, Thammasat University Hospital, Pathum Thani 12120, Thailand.
Boonpheng B; Division of Nephrology and Hypertension, Department of Medicine, Mayo Clinic, Jacksonville, FL 32224, USA.
Cheungpasitporn W; Department of Military and Community Medicine, Phramongkutklao College of Medicine, Bangkok 10400, Thailand.

Diseases ; 11(1)2023 Jan 27.

Article em En | MEDLINE | ID: mdl-36810532

Palavras-chave

AKI; HRS; acute kidney injury; cirrhosis; clustering; hepatorenal syndrome; machine learning

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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Prognostic_studies / Risk_factors_studies Idioma: En Revista: Diseases Ano de publicação: 2023 Tipo de documento: Article País de afiliação: Estados Unidos País de publicação: Suíça

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