Real-time prediction of intradialytic hypotension using machine learning and cloud computing infrastructure.

ABSTRACT:

Background

In maintenance hemodialysis patients, intradialytic hypotension (IDH) is a frequent complication that has been associated with poor clinical outcomes. Prediction of IDH may facilitate timely interventions and eventually reduce IDH rates.

Methods

We developed a machine learning model to predict IDH in in-center hemodialysis patients 15-75 min in advance. IDH was defined as systolic blood pressure (SBP) <90 mmHg. Demographic, clinical, treatment-related and laboratory data were retrieved from electronic health records and merged with intradialytic machine data that were sent in real-time to the cloud. For model development, dialysis sessions were randomly split into training (80%) and testing (20%) sets. The area under the receiver operating characteristic curve (AU

SUBMITTER: Zhang H 

PROVIDER: S-EPMC10310501 | biostudies-literature | 2023 Jun

REPOSITORIES: biostudies-literature