Implementing an AI-enhanced clinical decision support system for Stenotrophomonas maltophilia: a survey-based randomized controlled trial of antibiotic precision and impact on survival.

ABSTRACT:

Background

The World Health Organization has identified Stenotrophomonas maltophilia (SM) as a high-risk antibiotic-resistant pathogen. Notably, determining the effectiveness of current antibiotics against SM is challenging, leading to improper therapy and the spread of resistance. This study assessed how an artificial intelligence-clinical decision support system (AI-CDSS) utilizing mass spectrometry data to predict resistance enhances prescribing decisions and boosts survival.

Methods

This randomized controlled trial (ISRCTN16278872) involved 400 healthcare professionals, with 1,600 SM infections randomized in a 1:1 ratio to either standard practice (control, n = 800) or an AI-CDSS predicting resistance 1 day earlier (intervention, n = 800). Outcomes were assessed by healt

SUBMITTER: Lin TH 

PROVIDER: S-EPMC12551136 | biostudies-literature | 2025 Oct

REPOSITORIES: biostudies-literature