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Predictive modeling of fluid status in hemodialysis: model development and internal validation using the MONitoring dialysis outcomes (MONDO) global database

Background Optimized fluid management is crucial in dialysis care because extracellular volume overload drives adverse cardiovascular outcomes. At the same time, comorbidities such as inflammation and protein energy wasting lead to decreased muscle mass and intracellular water. Accurate assessment o...

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Principais autores: Sheng-Han Yueh, Jochen Raimann, Bernard Canaud, Meijiao Zhou, Xiaoling Ye, Ariella Mermelstein, Jeroen Kooman, Frank van der Sande, Len Usvyat, Peter Kotanko, Hanjie Zhang
Formato: Artigo
Idioma:Inglês
Publicado em: Taylor & Francis Group 2026-12-01
coleção:Renal Failure
Assuntos:
Hemodialysis
machine learning
bioimpedance spectroscopy
fluid management
Acesso em linha:https://www.tandfonline.com/doi/10.1080/0886022X.2026.2692105
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