Appropriate use of blood cultures in the emergency department through machine learning (ABC): study protocol for a randomised controlled non-inferiority trial.

ABSTRACT:

Introduction

The liberal use of blood cultures in emergency departments (EDs) leads to low yields and high numbers of false-positive results. False-positive, contaminated cultures are associated with prolonged hospital stays, increased antibiotic usage and even higher hospital mortality rates. This trial aims to investigate whether a recently developed and validated machine learning model for predicting blood culture outcomes can safely and effectively guide clinicians in withholding unnecessary blood culture analysis.

Methods and analysis

A randomised controlled, non-inferiority trial comparing current practice with a machine learning-guided approach. The primary objective is to determine whether the machine learning based approach is non-inferior to standard practice based

SUBMITTER: van der Zaag AY 

PROVIDER: S-EPMC11149153 | biostudies-literature | 2024 May

REPOSITORIES: biostudies-literature