Risk factors for bloodstream infections due to carbapenem-resistant Enterobacterales: a nested case-control-control study.

Background: Carbapenem-resistant Enterobacterales (CRE) bloodstream infections (BSIs) are a major threat to patients. To date, data on risk factors have been limited, with low internal and external validity. In this multicentre study, risk factors for CRE BSI were determined by comparison with two control groups: patients with carbapenem-susceptible Enterobacterales (CSE) BSI, and patients without Enterobacterales infection (uninfected patients).

Learning with an evolving medicine label: how artificial intelligence-based medication recommendation systems must adapt to changing medication labels.

Introduction: Artificial intelligence or machine learning (AI/ML) based systems can help personalize prescribing decisions for individual patients. The recommendations of these clinical decision support systems must relate to the "label" of the medicines involved. The label of a medicine is an approved guide that indicates how to prescribe the drug in a safe and effective manner.

Attributable mortality of infections caused by carbapenem-resistant Enterobacterales: results from a prospective, multinational case-control-control matched cohorts study (EURECA).

Objectives: To assess the mortality attributable to infections caused by carbapenem-resistant Enterobacterales (CRE) and to investigate the effect of clinical management on differences in observed outcomes in a multinational matched cohort study.

Methods: A prospective matched-cohorts study (NCT02709408) was performed in 50 European hospitals from March 2016 to November 2018. The main outcome was 30-day mortality with an active post-discharge follow-up when applied.

The Unseen Hand: AI-Based Prescribing Decision Support Tools and the Evaluation of Drug Safety and Effectiveness.

The use of artificial intelligence (AI)-based tools to guide prescribing decisions is full of promise and may enhance patient outcomes. These tools can perform actions such as choosing the 'safest' medication, choosing between competing medications, promoting de-prescribing or even predicting non-adherence. These tools can exist in a variety of formats; for example, they may be directly integrated into electronic medical records or they may exist in a stand-alone website accessible by a web browser.