Predicting blood pressure variability in hemodialysis using an explainable boosting machine model.

ABSTRACT:

Background

Intradialytic hypotension and hypertension significantly increase cardiovascular risk in hemodialysis patients, highlighting the need for effective monitoring systems. By predicting systolic blood pressure (SBP) values, monitoring capabilities can be improved beyond traditional event classification. Despite this potential advantage, current predictive models report a consistent error range (11-13 mmHg) and operate as black boxes. This study aims to develop a transparent SBP prediction model and evaluate its generalizability.

Methods

This retrospective study analyzed data from 524 patients across metropolitan and suburban hospital branches (2016-19), collecting hemodialysis parameters, vital signs and predialytic measurements. The Explainable Boosting Machine (EBM)

SUBMITTER: Huang WY 

PROVIDER: S-EPMC12712476 | biostudies-literature | 2025 Dec

REPOSITORIES: biostudies-literature