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

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.

Using machine learning to predict blood culture outcomes in the emergency department: a single-centre, retrospective, observational study.

Objectives: To develop predictive models for blood culture (BC) outcomes in an emergency department (ED) setting.

Design: Retrospective observational study.

Setting: ED of a large teaching hospital in the Netherlands between 1 September 2018 and 24 June 2020.