Karina-Doris Vihta

Oct 10, 2024 | nature.com | Karina-Doris Vihta |Koen B. Pouwels |Rebecca Guy |Katherine Henderson |Russell Hope |David A Clifton

AbstractPredicting antimicrobial resistance (AMR), a top global health threat, nationwide at an aggregate hospital level could help target interventions. Using machine learning, we exploit historical AMR and antimicrobial usage to predict future AMR. Antimicrobial use and AMR prevalence in bloodstream infections in hospitals in England were obtained per hospital group (Trust) and financial year (FY, April–March) for 22 pathogen–antibiotic combinations (FY2016-2017 to FY2021-2022).