Unsupervised machine learning analysis to identify patterns of ICU medication use for fluid overload prediction.

ABSTRACT:

Introduction

Intravenous (IV) medications are a fundamental cause of fluid overload (FO) in the intensive care unit (ICU); however, the association between IV medication use (including volume), administration timing, and FO occurrence remains unclear.

Methods

This retrospective cohort study included consecutive adults admitted to an ICU ≥72 hours with available fluid balance data. FO was defined as a positive fluid balance ≥7% of admission body weight within 72 hours of ICU admission. After reviewing medication administration record (MAR) data in three-hour periods, IV medication exposure was categorized into clusters using principal component analysis (PCA) and Restricted Boltzmann Machine (RBM). Medication regimens of patients with and without FO were compared within clust

SUBMITTER: Keats K 

PROVIDER: S-EPMC10984037 | biostudies-literature | 2024 Mar

REPOSITORIES: biostudies-literature