Exploring factors and models to predict post-dialysis volume overload status in maintenance hemodialysis patients based on pre-dialysis parameters

Pre-dialysis parameters, including prescribed UFV/weight ratio, OH, and dialysis US-B lines, were predictive factors for post-dialysis volume overload status. The Random Forest model based on these parameters could predict the post-dialysis volume overload status with relative accuracy and may provide a helpful guide to optimal prescribed UFV.

Authors

Publication Details

Journal
Clinical Nephrology
Published
2025-12-22
DOI
https://doi.org/10.5414/cn111762
Primary Topic
Dialysis and Renal Disease Management
Type
article
Field-Weighted Citation Impact
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article

Exploring factors and models to predict post-dialysis volume overload status in maintenance hemodialysis patients based on pre-dialysis parameters

Zheng Xiao-Yan, Lan-Ting Huang, Fu-yuan Hong, Bao-chun Lai et al.
Clinical Nephrology
Dialysis and Renal Disease Management
article

Exploring factors and models to predict post-dialysis volume overload status in maintenance hemodialysis patients based on pre-dialysis parameters

Zheng Xiao-Yan, Lan-Ting Huang, Fu-yuan Hong, Bao-chun Lai, Zhi-hong Zhang, Bing Xu, Qi Yang
article en

Abstract

Pre-dialysis parameters, including prescribed UFV/weight ratio, OH, and dialysis US-B lines, were predictive factors for post-dialysis volume overload status. The Random Forest model based on these parameters could predict the post-dialysis volume overload status with relative accuracy and may provide a helpful guide to optimal prescribed UFV.

Clinical NephrologyVol. 105(3)
Life in Land
Openalex Percentile: Top 32%
Dialysis and Renal Disease Management
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Exploring factors and models to predict post-dialysis volume overload status in maintenance hemodialysis patients based on pre-dialysis parameters — Zheng Xiao-Yan, Lan-Ting Huang, et al. · Clinical Nephrology (2025) | TGRS Research Map | TGRS